ctr_tf2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 点击率预估"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "点击率预估用来判断一条广告被用户点击的概率，对每次广告的点击做出预测，把用户最有可能点击的广告找出来，是广告技术最重要的算法之一。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据集下载"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"criteo.jpg\"\\>\n",
    "这次我们使用Kaggle上的[`Display Advertising Challenge`](https://www.kaggle.com/c/criteo-display-ad-challenge/)挑战的criteo数据集。\n",
    "\n",
    "下载数据集请在终端输入下面命令(脚本文件路径：./data/download.sh)："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "wget --no-check-certificate https://s3-eu-west-1.amazonaws.com/criteo-labs/dac.tar.gz\n",
    "\n",
    "tar zxf dac.tar.gz\n",
    "\n",
    "rm -f dac.tar.gz\n",
    "\n",
    "mkdir raw\n",
    "\n",
    "mv ./*.txt raw/\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "解压缩以后，train.txt文件11.7G，test.txt文件1.35G。\n",
    "\n",
    "数据量太大了，我们只使用前100万条数据。\n",
    "\n",
    "head -n 1000000 test.txt > test_sub100w.txt\n",
    "\n",
    "head -n 1000000 train.txt > train_sub100w.txt\n",
    "\n",
    "然后将文件名重新命名为train.txt和test.txt，文件位置不变。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data fields"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Label \n",
    "- Target variable that indicates if an ad was clicked (1) or not (0).\n",
    "\n",
    "#### I1-I13 \n",
    "- A total of 13 columns of integer features (mostly count features).\n",
    "\n",
    "#### C1-C26 \n",
    "- A total of 26 columns of categorical features. The values of these features have been hashed onto 32 bits for anonymization purposes. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据中含有Label字段，表示这条广告是否被点击，I1-I13一共13个数值特征（Dense Input），C1-C26共26个Categorical类别特征（Sparse Input）。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 网络模型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src='model.png'\\>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "模型包含三部分网络，一个是FFM(Field-aware Factorization Machines)，一个是FM(Factorization Machine)，另一个是DNN，其中FM网络包含GBDT和FM两个组件。通常在数据预处理的部分，需要做特征交叉组合等特征工程，以便找出帮助我们预测的特征出来，这绝对是技术活。\n",
    "\n",
    "这次我们跳过特征工程的步骤，把这些组件和深度神经网络组合在一起，将挑选特征的工作交给模型来处理。其中FFM使用了[`LibFFM`](https://www.csie.ntu.edu.tw/~cjlin/libffm/)，FM使用了[`LibFM`](http://www.libfm.org)，GBDT使用了[`LightGBM`](https://github.com/Microsoft/LightGBM)，当然你也可以使用[`xgboost`](http://xgboost.readthedocs.io/en/latest/)。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### GBDT"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "给入训练数据后，GBDT会训练出若干棵树，我们要使用的是GBDT中每棵树输出的叶子结点，将这些叶子结点作为categorical类别特征输入给FM。有关决策树的使用，请参照Facebook的这篇文章[`Practical Lessons from Predicting Clicks on Ads at Facebook`](http://quinonero.net/Publications/predicting-clicks-facebook.pdf)。\n",
    "<img src=\"facebook.png\"\\>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### FM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "FM用来解决数据量大并且特征稀疏下的特征组合问题，先来看看公式（只考虑二阶多项式的情况）：n代表样本的特征数量，$x_i$是第i个特征的值，$w_0$、$w_i$、$w_i$$_j$是模型参数。\n",
    "<img src=\"fm_formula.png\"\\>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从公式可以看出来这是在线性模型基础上，添加了特征组合$x_ix_j$，当然只有在特征$x_i$和$x_j$都不为0时才有意义。然而在实际的应用场景中，训练组合特征的参数是很困难的。因为输入数据普遍存在稀疏性，这导致$x_i$和$x_j$大部分情况都是0，而组合特征的参数$w_i$$_j$只有在特征不为0时才能训练出有意义的值。\n",
    "\n",
    "比如跟购物相关的特征中，女性可能会更关注化妆品或者首饰之类的物品，而男性可能更关注体育用品或者电子产品等商品，这说明特征组合训练是有意义的。而商品特征可能存在几百上千种分类，通常我们将类别特征转成One hot编码的形式，这样一个特征就要变成几百维的特征，再加上其他的分类特征，这导致输入的特征空间急剧膨胀，所以数据的稀疏性是实际问题中不可避免的挑战。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "为了解决二次项参数训练的问题，引入了矩阵分解的概念。在上一篇文章中我们讨论的是电影推荐系统，我们构造了用户特征向量和电影特征向量，通过两个特征向量的点积得到了用户对于某部电影的评分。如果将用户特征矩阵与电影特征矩阵相乘就会得到所有用户对所有影片的评分矩阵。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果将上面的过程反过来看，实际上对于评分矩阵，我们可以分解成用户矩阵和电影矩阵，而评分矩阵中每一个数据点就相当于上面讨论的组合特征的参数$w_i$$_j$。\n",
    "\n",
    "对于参数矩阵W，我们采用矩阵分解的方法，将每一个参数$w_i$$_j$分解成两个向量（称之为隐向量）的点积。这样矩阵就可以分解为$W=V^TV$，而每个参数$w_i$$_j$=⟨$v_i$,$v_j$⟩，$v_i$是第i维特征的隐向量，这样FM的二阶公式就变成：\n",
    "<img src=\"fm_formula2.png\"\\>\n",
    "\n",
    "这就是FM模型的思想。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "将GBDT输出的叶子节点作为训练数据的输入，来训练FM模型。这样对于我们的FM网络，需要训练GBDT和FM。看得出来，这次我们的点击率预测网络要复杂了许多，影响最终结果的因素和超参更多了。关于FM和GBDT两个组件的训练我们会在下文进行说明。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### FFM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "接下来需要训练FFM模型。FFM在FM的基础上增加了一个Field的概念，比如说一个商品字段，是一个分类特征，可以分成很多不同的feature，但是这些feature都属于同一个Field，或者说同一个categorical的分类特征都可以放到同一个Field。\n",
    "\n",
    "这可以看成是1对多的关系，打个比方，比如职业字段，这是一个特征，经过One Hot以后，变成了N个特征。那这N个特征其实都属于职业，所以职业就是一个Field。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们要通过特征组合来训练隐向量，这样每一维特征$x_i$，都会与其他特征的每一种Field $f_j$学习一个隐向量$v_{i,f_j}$。也就是说，隐向量不仅与特征有关，还与Field有关。模型的公式：\n",
    "<img src=\"ffm_formula.png\"\\>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DNN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们来看DNN的部分。将输入数据分成两部分，一部分是数值特征（Dense Input），一部分是类别特征（Sparse Input）。我们仍然不适用One Hot编码，将类别特征传入嵌入层，得到多个嵌入向量，再将这些嵌入向量和数值特征连接在一起，传入全连接层，一共连接三层全连接层，使用Relu激活函数。然后再将第三层全连接的输出和FFM、FM的全连接层的输出连接在一起，传入最后一层全连接层。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们要学习的目标Label表示广告是否被点击了，只有1（点击）和0（没有点击）两种状态。所以我们网络的最后一层要做Logistic回归，在最后一层全连接层使用Sigmoid激活函数，得到广告被点击的概率。\n",
    "\n",
    "使用LogLoss作为损失函数，FTRL作为学习算法。\n",
    "\n",
    "FTRL有关的Paper：[`Ad_click_prediction_a_view_from_the_trenches`](https://www.researchgate.net/publication/262412214_Ad_click_prediction_a_view_from_the_trenches)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### LibFFM和LibFM的代码我做了修改，请使用代码库中我的相关代码。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 预处理数据集"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 生成神经网络的输入\n",
    "- 生成FFM的输入\n",
    "- 生成GBDT的输入"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "首先要为DNN、FFM和GBDT的输入做预处理。对于数值特征，我们将I1-I13转成0-1之间的小数。类别特征我们将某类别使用次数少于cutoff（超参）的忽略掉，留下使用次数多的feature作为某类别字段的特征，然后将这些特征以各自字段为组进行编号。\n",
    "\n",
    "比如有C1和C2两个类别字段，C1下面有特征a（大于cutoff次）、b（少于cutoff次）、c（大于cutoff次），C2下面有特征x和y（均大于cutoff次），这样留下来的特征就是C1：a、c和C2：x、y。然后以各自字段为分组进行编号，对于C1字段，a和c的特征id对应0和1；对于C2字段，x和y也是0和1。\n",
    "\n",
    "对于类别特征的输入数据处理，FFM和GBDT各不相同，我们分别来说。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### GBDT"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "GBDT的处理要简单一些，C1-C26每个字段各自的特征id值作为输入即可。\n",
    "GBDT的输入数据格式是：Label I1-I13 C1-C26\n",
    "所以实际输入可能是这样：0 小数1 小数2 ~ 小数13 1（C1特征Id） 0（C2特征Id） ~ C26特征Id\n",
    "其中C1特征Id是1，说明此处C1字段的feature是c，而C2字段的feature是x。\n",
    "\n",
    "下面是一段生成的真实数据：\n",
    "0\t0.05\t0.004983\t0.05\t0\t0.021594\t0.008\t0.15\t0.04\t0.362\t0.166667\t0.2\t0\t0.04\t2\t3\t0\t0\t1\t1\t0\t3\t1\t0\t0\t0\t0\t3\t0\t0\t1\t4\t1\t3\t0\t0\t2\t0\t1\t0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "很抱歉，我的造句能力实在很差，要是上面一段文字看的你很混乱的话，那就直接看代码吧：）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### FFM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "FFM的输入数据要复杂一些，详细可以参看官方[`Github`](https://github.com/guestwalk/libffm)上的说明，摘抄如下：\n",
    "\n",
    "It is important to understand the difference between `field` and `feature`. For example, if we have a raw data like this:\n",
    "\n",
    "    Click  Advertiser  Publisher\n",
    "    =====  ==========  =========\n",
    "    0        Nike        CNN\n",
    "    1        ESPN        BBC\n",
    "\n",
    "Here, we have \n",
    "\n",
    "    * 2 fields: Advertiser and Publisher\n",
    "    * 4 features: Advertiser-Nike, Advertiser-ESPN, Publisher-CNN, Publisher-BBC\n",
    "\n",
    "Usually you will need to build two dictionares, one for field and one for features, like this:\n",
    "    \n",
    "    DictField[Advertiser] -> 0\n",
    "    DictField[Publisher]  -> 1\n",
    "    \n",
    "    DictFeature[Advertiser-Nike] -> 0\n",
    "    DictFeature[Publisher-CNN]   -> 1\n",
    "    DictFeature[Advertiser-ESPN] -> 2\n",
    "    DictFeature[Publisher-BBC]   -> 3\n",
    "\n",
    "Then, you can generate FFM format data:\n",
    "\n",
    "    0 0:0:1 1:1:1\n",
    "    1 0:2:1 1:3:1\n",
    "\n",
    "Note that because these features are categorical, the values here are all ones.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "fields应该很好理解，features的划分跟之前GBDT有些不一样，在刚刚GBDT的处理中我们是每个类别内独立编号，C1有features 0~n，C2有features 0~n。而这次FFM是所有的features统一起来编号。你看它的例子，C1是Advertiser，有两个feature，C2是Publisher，有两个feature，统一起来编号就是0~3。而在GBDT我们要独立编号的，看起来像这样：\n",
    "\n",
    "    DictFeature[Advertiser-Nike] -> 0\n",
    "    DictFeature[Advertiser-ESPN] -> 1\n",
    "    DictFeature[Publisher-CNN]   -> 0\n",
    "    DictFeature[Publisher-BBC]   -> 1 \n",
    "现在我们假设有第三条数据，看看如何构造FFM的输入数据：\n",
    "\n",
    "    Click  Advertiser  Publisher\n",
    "    =====  ==========  =========\n",
    "    0        Nike        CNN\n",
    "    1        ESPN        BBC\n",
    "    0        Lining      CNN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "按照规则，应该是像下面这样：\n",
    "\n",
    "    DictFeature[Advertiser-Nike]   -> 0\n",
    "    DictFeature[Publisher-CNN]     -> 1\n",
    "    DictFeature[Advertiser-ESPN]   -> 2\n",
    "    DictFeature[Publisher-BBC]     -> 3\n",
    "    DictFeature[Advertiser-Lining] -> 4\n",
    "在我们这次FFM的输入数据处理中，跟上面略有些区别，每个类别编号以后，下一个类别继续编号，所以最终的features编号是这样的：\n",
    "\n",
    "    DictFeature[Advertiser-Nike]   -> 0\n",
    "    DictFeature[Advertiser-ESPN]   -> 1\n",
    "    DictFeature[Advertiser-Lining] -> 2\n",
    "    DictFeature[Publisher-CNN]     -> 3\n",
    "    DictFeature[Publisher-BBC]     -> 4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对于我们的数据是从I1开始编号的，从I1-I13，所以C1的编号要从加13开始。\n",
    "\n",
    "这是一条来自真实的FFM输入数据：\n",
    "0\t0:0:0.05\t1:1:0.004983\t2:2:0.05\t3:3:0\t4:4:0.021594\t5:5:0.008\t6:6:0.15\t7:7:0.04\t8:8:0.362\t9:9:0.166667\t10:10:0.2\t11:11:0\t12:12:0.04\t13:15:1\t14:29:1\t15:64:1\t16:76:1\t17:92:1\t18:101:1\t19:107:1\t20:122:1\t21:131:1\t22:133:1\t23:143:1\t24:166:1\t25:179:1\t26:209:1\t27:216:1\t28:243:1\t29:260:1\t30:273:1\t31:310:1\t32:317:1\t33:318:1\t34:333:1\t35:340:1\t36:348:1\t37:368:1\t38:381:1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DNN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "DNN的输入数据就没有那么复杂了，仍然是I1-I13的小数和C1-C26的统一编号，就像FFM一样，只是不需要从加13开始，最后是Label。\n",
    "真实数据就像这样：\n",
    "0.05,0.004983,0.05,0,0.021594,0.008,0.15,0.04,0.362,0.166667,0.2,0,0.04,2,16,51,63,79,88,94,109,118,120,130,153,166,196,203,230,247,260,297,304,305,320,\n",
    "327,335,355,368,0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "要说明的就这么多了，我们来看看代码吧，因为要同时生成训练数据、验证数据和测试数据，所以要运行一段时间。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "import click\n",
    "import random\n",
    "import collections\n",
    "\n",
    "import numpy as np\n",
    "import lightgbm as lgb\n",
    "import json\n",
    "import pandas as pd\n",
    "from sklearn.metrics import mean_squared_error\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "def save_params(params):\n",
    "    \"\"\"\n",
    "    Save parameters to file\n",
    "    \"\"\"\n",
    "    pickle.dump(params, open('params.p', 'wb'))\n",
    "\n",
    "\n",
    "def load_params():\n",
    "    \"\"\"\n",
    "    Load parameters from file\n",
    "    \"\"\"\n",
    "    return pickle.load(open('params.p', mode='rb'))\n",
    "\n",
    "\n",
    "def save_params_with_name(params, name):\n",
    "    \"\"\"\n",
    "    Save parameters to file\n",
    "    \"\"\"\n",
    "    pickle.dump(params, open('{}.p'.format(name), 'wb'))\n",
    "\n",
    "\n",
    "def load_params_with_name(name):\n",
    "    \"\"\"\n",
    "    Load parameters from file\n",
    "    \"\"\"\n",
    "    return pickle.load(open('{}.p'.format(name), mode='rb'))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "以下代码来自百度deep_fm的[`preprocess.py`](https://github.com/PaddlePaddle/models/blob/develop/deep_fm/preprocess.py)，稍稍添了些代码，我就不重复造轮子了：）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# There are 13 integer features and 26 categorical features\n",
    "continous_features = range(1, 14)\n",
    "categorial_features = range(14, 40)\n",
    "\n",
    "# Clip integer features. The clip point for each integer feature\n",
    "# is derived from the 95% quantile of the total values in each feature\n",
    "continous_clip = [20, 600, 100, 50, 64000, 500, 100, 50, 500, 10, 10, 10, 50]\n",
    "\n",
    "class ContinuousFeatureGenerator:\n",
    "    \"\"\"\n",
    "    Normalize the integer features to [0, 1] by min-max normalization\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, num_feature):\n",
    "        self.num_feature = num_feature\n",
    "        self.min = [sys.maxsize] * num_feature\n",
    "        self.max = [-sys.maxsize] * num_feature\n",
    "\n",
    "    def build(self, datafile, continous_features):\n",
    "        with open(datafile, 'r') as f:\n",
    "            for line in f:\n",
    "                features = line.rstrip('\\n').split('\\t')\n",
    "                for i in range(0, self.num_feature):\n",
    "                    val = features[continous_features[i]]\n",
    "                    if val != '':\n",
    "                        val = int(val)\n",
    "                        if val > continous_clip[i]:\n",
    "                            val = continous_clip[i]\n",
    "                        self.min[i] = min(self.min[i], val)\n",
    "                        self.max[i] = max(self.max[i], val)\n",
    "\n",
    "    def gen(self, idx, val):\n",
    "        if val == '':\n",
    "            return 0.0\n",
    "        val = float(val)\n",
    "        return (val - self.min[idx]) / (self.max[idx] - self.min[idx])\n",
    "\n",
    "class CategoryDictGenerator:\n",
    "    \"\"\"\n",
    "    Generate dictionary for each of the categorical features\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, num_feature):\n",
    "        self.dicts = []\n",
    "        self.num_feature = num_feature\n",
    "        for i in range(0, num_feature):\n",
    "            self.dicts.append(collections.defaultdict(int))\n",
    "\n",
    "    def build(self, datafile, categorial_features, cutoff=0):\n",
    "        with open(datafile, 'r') as f:\n",
    "            for line in f:\n",
    "                features = line.rstrip('\\n').split('\\t')\n",
    "                for i in range(0, self.num_feature):\n",
    "                    if features[categorial_features[i]] != '':\n",
    "                        self.dicts[i][features[categorial_features[i]]] += 1\n",
    "        for i in range(0, self.num_feature):\n",
    "            self.dicts[i] = filter(lambda x: x[1] >= cutoff,\n",
    "                                   self.dicts[i].items())\n",
    "\n",
    "            self.dicts[i] = sorted(self.dicts[i], key=lambda x: (-x[1], x[0]))\n",
    "            vocabs, _ = list(zip(*self.dicts[i]))\n",
    "            self.dicts[i] = dict(zip(vocabs, range(1, len(vocabs) + 1)))\n",
    "            self.dicts[i]['<unk>'] = 0\n",
    "\n",
    "    def gen(self, idx, key):\n",
    "        if key not in self.dicts[idx]:\n",
    "            res = self.dicts[idx]['<unk>']\n",
    "        else:\n",
    "            res = self.dicts[idx][key]\n",
    "        return res\n",
    "\n",
    "    def dicts_sizes(self):\n",
    "        return list(map(len, self.dicts))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def preprocess(datadir, outdir):\n",
    "    \"\"\"\n",
    "    All the 13 integer features are normalzied to continous values and these\n",
    "    continous features are combined into one vecotr with dimension 13.\n",
    "\n",
    "    Each of the 26 categorical features are one-hot encoded and all the one-hot\n",
    "    vectors are combined into one sparse binary vector.\n",
    "    \"\"\"\n",
    "    dists = ContinuousFeatureGenerator(len(continous_features))\n",
    "    dists.build(os.path.join(datadir, 'train.txt'), continous_features)\n",
    "\n",
    "    dicts = CategoryDictGenerator(len(categorial_features))\n",
    "    dicts.build(\n",
    "        os.path.join(datadir, 'train.txt'), categorial_features, cutoff=200)#200 50\n",
    "\n",
    "    dict_sizes = dicts.dicts_sizes()\n",
    "    categorial_feature_offset = [0]\n",
    "    for i in range(1, len(categorial_features)):\n",
    "        offset = categorial_feature_offset[i - 1] + dict_sizes[i - 1]\n",
    "        categorial_feature_offset.append(offset)\n",
    "\n",
    "    random.seed(0)\n",
    "\n",
    "    # 90% of the data are used for training, and 10% of the data are used\n",
    "    # for validation.\n",
    "    train_ffm = open(os.path.join(outdir, 'train_ffm.txt'), 'w')\n",
    "    valid_ffm = open(os.path.join(outdir, 'valid_ffm.txt'), 'w')\n",
    "\n",
    "    train_lgb = open(os.path.join(outdir, 'train_lgb.txt'), 'w')\n",
    "    valid_lgb = open(os.path.join(outdir, 'valid_lgb.txt'), 'w')\n",
    "\n",
    "    with open(os.path.join(outdir, 'train.txt'), 'w') as out_train:\n",
    "        with open(os.path.join(outdir, 'valid.txt'), 'w') as out_valid:\n",
    "            with open(os.path.join(datadir, 'train.txt'), 'r') as f:\n",
    "                for line in f:\n",
    "                    features = line.rstrip('\\n').split('\\t')\n",
    "                    continous_feats = []\n",
    "                    continous_vals = []\n",
    "                    for i in range(0, len(continous_features)):\n",
    "\n",
    "                        val = dists.gen(i, features[continous_features[i]])\n",
    "                        continous_vals.append(\n",
    "                            \"{0:.6f}\".format(val).rstrip('0').rstrip('.'))\n",
    "                        continous_feats.append(\n",
    "                            \"{0:.6f}\".format(val).rstrip('0').rstrip('.'))#('{0}'.format(val))\n",
    "\n",
    "                    categorial_vals = []\n",
    "                    categorial_lgb_vals = []\n",
    "                    for i in range(0, len(categorial_features)):\n",
    "                        val = dicts.gen(i, features[categorial_features[i]]) + categorial_feature_offset[i]\n",
    "                        categorial_vals.append(str(val))\n",
    "                        val_lgb = dicts.gen(i, features[categorial_features[i]])\n",
    "                        categorial_lgb_vals.append(str(val_lgb))\n",
    "\n",
    "                    continous_vals = ','.join(continous_vals)\n",
    "                    categorial_vals = ','.join(categorial_vals)\n",
    "                    label = features[0]\n",
    "                    if random.randint(0, 9999) % 10 != 0:\n",
    "                        out_train.write(','.join(\n",
    "                            [continous_vals, categorial_vals, label]) + '\\n')\n",
    "                        train_ffm.write('\\t'.join(label) + '\\t')\n",
    "                        train_ffm.write('\\t'.join(\n",
    "                            ['{}:{}:{}'.format(ii, ii, val) for ii,val in enumerate(continous_vals.split(','))]) + '\\t')\n",
    "                        train_ffm.write('\\t'.join(\n",
    "                            ['{}:{}:1'.format(ii + 13, str(np.int32(val) + 13)) for ii, val in enumerate(categorial_vals.split(','))]) + '\\n')\n",
    "                        \n",
    "                        train_lgb.write('\\t'.join(label) + '\\t')\n",
    "                        train_lgb.write('\\t'.join(continous_feats) + '\\t')\n",
    "                        train_lgb.write('\\t'.join(categorial_lgb_vals) + '\\n')\n",
    "\n",
    "                    else:\n",
    "                        out_valid.write(','.join(\n",
    "                            [continous_vals, categorial_vals, label]) + '\\n')\n",
    "                        valid_ffm.write('\\t'.join(label) + '\\t')\n",
    "                        valid_ffm.write('\\t'.join(\n",
    "                            ['{}:{}:{}'.format(ii, ii, val) for ii,val in enumerate(continous_vals.split(','))]) + '\\t')\n",
    "                        valid_ffm.write('\\t'.join(\n",
    "                            ['{}:{}:1'.format(ii + 13, str(np.int32(val) + 13)) for ii, val in enumerate(categorial_vals.split(','))]) + '\\n')\n",
    "                                                \n",
    "                        valid_lgb.write('\\t'.join(label) + '\\t')\n",
    "                        valid_lgb.write('\\t'.join(continous_feats) + '\\t')\n",
    "                        valid_lgb.write('\\t'.join(categorial_lgb_vals) + '\\n')\n",
    "                        \n",
    "    train_ffm.close()\n",
    "    valid_ffm.close()\n",
    "\n",
    "    train_lgb.close()\n",
    "    valid_lgb.close()\n",
    "\n",
    "    test_ffm = open(os.path.join(outdir, 'test_ffm.txt'), 'w')\n",
    "    test_lgb = open(os.path.join(outdir, 'test_lgb.txt'), 'w')\n",
    "\n",
    "    with open(os.path.join(outdir, 'test.txt'), 'w') as out:\n",
    "        with open(os.path.join(datadir, 'test.txt'), 'r') as f:\n",
    "            for line in f:\n",
    "                features = line.rstrip('\\n').split('\\t')\n",
    "\n",
    "                continous_feats = []\n",
    "                continous_vals = []\n",
    "                for i in range(0, len(continous_features)):\n",
    "                    val = dists.gen(i, features[continous_features[i] - 1])\n",
    "                    continous_vals.append(\n",
    "                        \"{0:.6f}\".format(val).rstrip('0').rstrip('.'))\n",
    "                    continous_feats.append(\n",
    "                            \"{0:.6f}\".format(val).rstrip('0').rstrip('.'))#('{0}'.format(val))\n",
    "\n",
    "                categorial_vals = []\n",
    "                categorial_lgb_vals = []\n",
    "                for i in range(0, len(categorial_features)):\n",
    "                    val = dicts.gen(i,\n",
    "                                    features[categorial_features[i] -\n",
    "                                             1]) + categorial_feature_offset[i]\n",
    "                    categorial_vals.append(str(val))\n",
    "\n",
    "                    val_lgb = dicts.gen(i, features[categorial_features[i] - 1])\n",
    "                    categorial_lgb_vals.append(str(val_lgb))\n",
    "\n",
    "                continous_vals = ','.join(continous_vals)\n",
    "                categorial_vals = ','.join(categorial_vals)\n",
    "\n",
    "                out.write(','.join([continous_vals, categorial_vals]) + '\\n')\n",
    "                \n",
    "                test_ffm.write('\\t'.join(['{}:{}:{}'.format(ii, ii, val) for ii,val in enumerate(continous_vals.split(','))]) + '\\t')\n",
    "                test_ffm.write('\\t'.join(\n",
    "                    ['{}:{}:1'.format(ii + 13, str(np.int32(val) + 13)) for ii, val in enumerate(categorial_vals.split(','))]) + '\\n')\n",
    "                                                                \n",
    "                test_lgb.write('\\t'.join(continous_feats) + '\\t')\n",
    "                test_lgb.write('\\t'.join(categorial_lgb_vals) + '\\n')\n",
    "\n",
    "    test_ffm.close()\n",
    "    test_lgb.close()\n",
    "    return dict_sizes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "dict_sizes = preprocess('./data/raw','./data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "save_params_with_name((dict_sizes), 'dict_sizes') #pickle.dump((dict_sizes), open('dict_sizes.p', 'wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dict_sizes = load_params_with_name('dict_sizes') #pickle.load(open('dict_sizes.p', mode='rb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8496"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(dict_sizes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 训练FFM\n",
    "\n",
    "数据准备好了，开始调用LibFFM，训练FFM模型。\n",
    "\n",
    "learning rate是0.1，迭代32次，训练好后保存的模型文件是model_ffm。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import subprocess, sys, os, time\n",
    "\n",
    "NR_THREAD = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['First check if the text file has already been converted to binary format (1.3 seconds)\\n',\n",
       " 'Binary file found. Skip converting text to binary\\n',\n",
       " 'First check if the text file has already been converted to binary format (0.2 seconds)\\n',\n",
       " 'Binary file found. Skip converting text to binary\\n',\n",
       " 'iter   tr_logloss   va_logloss      tr_time\\n',\n",
       " '   1      0.49339      0.48196         12.8\\n',\n",
       " '   2      0.47621      0.47651         25.9\\n',\n",
       " '   3      0.47149      0.47433         39.0\\n',\n",
       " '   4      0.46858      0.47277         51.2\\n',\n",
       " '   5      0.46630      0.47168         63.0\\n',\n",
       " '   6      0.46447      0.47092         74.7\\n',\n",
       " '   7      0.46269      0.47038         86.4\\n',\n",
       " '   8      0.46113      0.47000         98.0\\n',\n",
       " '   9      0.45960      0.46960        109.6\\n',\n",
       " '  10      0.45811      0.46940        121.2\\n',\n",
       " '  11      0.45660      0.46913        132.5\\n',\n",
       " '  12      0.45509      0.46899        144.3\\n',\n",
       " '  13      0.45366      0.46903\\n',\n",
       " 'Auto-stop. Use model at 12th iteration.\\n']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmd = './libffm/libffm/ffm-train --auto-stop -r 0.1 -t 32 -s {nr_thread} -p ./data/valid_ffm.txt ./data/train_ffm.txt model_ffm'.format(nr_thread=NR_THREAD) \n",
    "os.popen(cmd).readlines()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "FFM模型训练好了，我们把训练、验证和测试数据输入给FFM，得到FFM层的输出，输出的文件名为*.out.logit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['logloss = 0.45308\\n']"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmd = './libffm/libffm/ffm-predict ./data/train_ffm.txt model_ffm tr_ffm.out'.format(nr_thread=NR_THREAD) \n",
    "os.popen(cmd).readlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['logloss = 0.46899\\n']"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmd = './libffm/libffm/ffm-predict ./data/valid_ffm.txt model_ffm va_ffm.out'.format(nr_thread=NR_THREAD) \n",
    "os.popen(cmd).readlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['done!\\n']"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmd = './libffm/libffm/ffm-predict ./data/test_ffm.txt model_ffm te_ffm.out true'.format(nr_thread=NR_THREAD) \n",
    "os.popen(cmd).readlines()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 训练GBDT"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "现在调用LightGBM训练GBDT模型，因为决策树较容易过拟合，我们设置树的个数为32，叶子节点数设为30，深度就不设置了，学习率设为0.05。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def lgb_pred(tr_path, va_path, _sep = '\\t', iter_num = 32):\n",
    "    # load or create your dataset\n",
    "    print('Load data...')\n",
    "    df_train = pd.read_csv(tr_path, header=None, sep=_sep)\n",
    "    df_test = pd.read_csv(va_path, header=None, sep=_sep)\n",
    "    \n",
    "    y_train = df_train[0].values\n",
    "    y_test = df_test[0].values\n",
    "    X_train = df_train.drop(0, axis=1).values\n",
    "    X_test = df_test.drop(0, axis=1).values\n",
    "    \n",
    "    # create dataset for lightgbm\n",
    "    lgb_train = lgb.Dataset(X_train, y_train)\n",
    "    lgb_eval = lgb.Dataset(X_test, y_test, reference=lgb_train)\n",
    "    \n",
    "    # specify your configurations as a dict\n",
    "    params = {\n",
    "        'task': 'train',\n",
    "        'boosting_type': 'gbdt',\n",
    "        'objective': 'binary',\n",
    "        'metric': {'l2', 'auc', 'logloss'},\n",
    "        'num_leaves': 30,\n",
    "#         'max_depth': 7,\n",
    "        'num_trees': 32,\n",
    "        'learning_rate': 0.05,\n",
    "        'feature_fraction': 0.9,\n",
    "        'bagging_fraction': 0.8,\n",
    "        'bagging_freq': 5,\n",
    "        'verbose': 0\n",
    "    }\n",
    "    \n",
    "    print('Start training...')\n",
    "    # train\n",
    "    gbm = lgb.train(params,\n",
    "                    lgb_train,\n",
    "                    num_boost_round=iter_num,\n",
    "                    valid_sets=lgb_eval,\n",
    "                    feature_name=[\"I1\",\"I2\",\"I3\",\"I4\",\"I5\",\"I6\",\"I7\",\"I8\",\"I9\",\"I10\",\"I11\",\"I12\",\"I13\",\"C1\",\"C2\",\"C3\",\"C4\",\"C5\",\"C6\",\"C7\",\"C8\",\"C9\",\"C10\",\"C11\",\"C12\",\"C13\",\"C14\",\"C15\",\"C16\",\"C17\",\"C18\",\"C19\",\"C20\",\"C21\",\"C22\",\"C23\",\"C24\",\"C25\",\"C26\"],\n",
    "                    categorical_feature=[\"C1\",\"C2\",\"C3\",\"C4\",\"C5\",\"C6\",\"C7\",\"C8\",\"C9\",\"C10\",\"C11\",\"C12\",\"C13\",\"C14\",\"C15\",\"C16\",\"C17\",\"C18\",\"C19\",\"C20\",\"C21\",\"C22\",\"C23\",\"C24\",\"C25\",\"C26\"],\n",
    "                    early_stopping_rounds=5)\n",
    "    \n",
    "    print('Save model...')\n",
    "    # save model to file\n",
    "    gbm.save_model('lgb_model.txt')\n",
    "    \n",
    "    print('Start predicting...')\n",
    "    # predict\n",
    "    y_pred = gbm.predict(X_test, num_iteration=gbm.best_iteration)\n",
    "    # eval\n",
    "    print('The rmse of prediction is:', mean_squared_error(y_test, y_pred) ** 0.5)\n",
    "\n",
    "    return gbm,y_pred,X_train,y_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Load data...\n",
      "Start training...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Applications/anaconda/envs/tensorflow1.0/lib/python3.5/site-packages/lightgbm/engine.py:99: UserWarning: Found `num_trees` in params. Will use it instead of argument\n",
      "  warnings.warn(\"Found `{}` in params. Will use it instead of argument\".format(alias))\n",
      "/Applications/anaconda/envs/tensorflow1.0/lib/python3.5/site-packages/lightgbm/basic.py:1029: UserWarning: categorical_feature in Dataset is overrided. New categorical_feature is ['C1', 'C10', 'C11', 'C12', 'C13', 'C14', 'C15', 'C16', 'C17', 'C18', 'C19', 'C2', 'C20', 'C21', 'C22', 'C23', 'C24', 'C25', 'C26', 'C3', 'C4', 'C5', 'C6', 'C7', 'C8', 'C9']\n",
      "  warnings.warn('categorical_feature in Dataset is overrided. New categorical_feature is {}'.format(sorted(list(categorical_feature))))\n",
      "/Applications/anaconda/envs/tensorflow1.0/lib/python3.5/site-packages/lightgbm/basic.py:668: UserWarning: categorical_feature in param dict is overrided.\n",
      "  warnings.warn('categorical_feature in param dict is overrided.')\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l2: 0.241954\tvalid_0's auc: 0.70607\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l2: 0.234704\tvalid_0's auc: 0.715608\n",
      "[3]\tvalid_0's l2: 0.228139\tvalid_0's auc: 0.717791\n",
      "[4]\tvalid_0's l2: 0.222168\tvalid_0's auc: 0.72273\n",
      "[5]\tvalid_0's l2: 0.216728\tvalid_0's auc: 0.724065\n",
      "[6]\tvalid_0's l2: 0.211819\tvalid_0's auc: 0.725036\n",
      "[7]\tvalid_0's l2: 0.207316\tvalid_0's auc: 0.727427\n",
      "[8]\tvalid_0's l2: 0.203296\tvalid_0's auc: 0.728583\n",
      "[9]\tvalid_0's l2: 0.199582\tvalid_0's auc: 0.730092\n",
      "[10]\tvalid_0's l2: 0.196185\tvalid_0's auc: 0.730792\n",
      "[11]\tvalid_0's l2: 0.193063\tvalid_0's auc: 0.732316\n",
      "[12]\tvalid_0's l2: 0.190268\tvalid_0's auc: 0.733773\n",
      "[13]\tvalid_0's l2: 0.187697\tvalid_0's auc: 0.734782\n",
      "[14]\tvalid_0's l2: 0.185351\tvalid_0's auc: 0.735636\n",
      "[15]\tvalid_0's l2: 0.183215\tvalid_0's auc: 0.736346\n",
      "[16]\tvalid_0's l2: 0.181241\tvalid_0's auc: 0.737393\n",
      "[17]\tvalid_0's l2: 0.179468\tvalid_0's auc: 0.737709\n",
      "[18]\tvalid_0's l2: 0.177829\tvalid_0's auc: 0.739096\n",
      "[19]\tvalid_0's l2: 0.176326\tvalid_0's auc: 0.740135\n",
      "[20]\tvalid_0's l2: 0.174948\tvalid_0's auc: 0.741065\n",
      "[21]\tvalid_0's l2: 0.173675\tvalid_0's auc: 0.742165\n",
      "[22]\tvalid_0's l2: 0.172499\tvalid_0's auc: 0.742672\n",
      "[23]\tvalid_0's l2: 0.171471\tvalid_0's auc: 0.743246\n",
      "[24]\tvalid_0's l2: 0.17045\tvalid_0's auc: 0.744415\n",
      "[25]\tvalid_0's l2: 0.169582\tvalid_0's auc: 0.744792\n",
      "[26]\tvalid_0's l2: 0.168746\tvalid_0's auc: 0.745478\n",
      "[27]\tvalid_0's l2: 0.167966\tvalid_0's auc: 0.746282\n",
      "[28]\tvalid_0's l2: 0.167264\tvalid_0's auc: 0.74675\n",
      "[29]\tvalid_0's l2: 0.166582\tvalid_0's auc: 0.747429\n",
      "[30]\tvalid_0's l2: 0.16594\tvalid_0's auc: 0.748392\n",
      "[31]\tvalid_0's l2: 0.165364\tvalid_0's auc: 0.748986\n",
      "[32]\tvalid_0's l2: 0.164844\tvalid_0's auc: 0.749362\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[32]\tvalid_0's l2: 0.164844\tvalid_0's auc: 0.749362\n",
      "Save model...\n",
      "Start predicting...\n",
      "The rmse of prediction is: 0.406009502303\n"
     ]
    }
   ],
   "source": [
    "gbm,y_pred,X_train ,y_train = lgb_pred('./data/train_lgb.txt', './data/valid_lgb.txt', '\\t', 256)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 查看每个特征的重要程度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 15,   0,  30,  10,  12,  79,  31,  15,  14,   0,  44,   0,  29,\n",
       "         0,  16,   0,  65,   0,   0,  32,   0,   0,  29,  30,  10, 120,\n",
       "        30, 165,  19,  11,  69,   1,   0,   2,   0,   6,  39,   0,   5])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gbm.feature_importance()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  69634.31561279,       0.        ,   17624.44689941,\n",
       "          4734.61398315,   10529.7180481 ,  199794.76257324,\n",
       "         94191.14331055,   13543.23699951,   10014.74700928,\n",
       "             0.        ,  191050.53414917,       0.        ,\n",
       "         28020.85171509,       0.        ,    6852.7729187 ,\n",
       "             0.        ,   32251.70903015,       0.        ,\n",
       "             0.        ,   14341.38494873,       0.        ,\n",
       "             0.        ,   11129.02203369,   12486.21105957,\n",
       "          5218.96902466,   99722.85806274,   23106.2180481 ,\n",
       "         79130.2718811 ,   10490.07904053,   17757.50100708,\n",
       "         34302.44396973,     424.67401123,       0.        ,\n",
       "           882.20599365,       0.        ,    3156.61196899,\n",
       "         15901.01004028,       0.        ,    3397.2270813 ])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gbm.feature_importance(\"gain\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 我们把每个特征的重要程度排个序看看"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ret_feat_impt(gbm):\n",
    "    gain = gbm.feature_importance(\"gain\").reshape(-1, 1) / sum(gbm.feature_importance(\"gain\"))\n",
    "    col = np.array(gbm.feature_name()).reshape(-1, 1)\n",
    "    return sorted(np.column_stack((col, gain)),key=lambda x: x[1],reverse=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array(['I6', '0.1978774213012332'],\n",
       "       dtype='<U32'), array(['I11', '0.1892171073393491'],\n",
       "       dtype='<U32'), array(['C13', '0.09876586224832032'],\n",
       "       dtype='<U32'), array(['I7', '0.09328723289667494'],\n",
       "       dtype='<U32'), array(['C15', '0.07837089393651243'],\n",
       "       dtype='<U32'), array(['I1', '0.06896606612740637'],\n",
       "       dtype='<U32'), array(['C18', '0.03397325870627491'],\n",
       "       dtype='<U32'), array(['C4', '0.03194220375573926'],\n",
       "       dtype='<U32'), array(['I13', '0.027751948092299045'],\n",
       "       dtype='<U32'), array(['C14', '0.022884477973766117'],\n",
       "       dtype='<U32'), array(['C17', '0.01758709018584479'],\n",
       "       dtype='<U32'), array(['I3', '0.01745531293913725'],\n",
       "       dtype='<U32'), array(['C24', '0.015748415135270675'],\n",
       "       dtype='<U32'), array(['C7', '0.014203757070472703'],\n",
       "       dtype='<U32'), array(['I8', '0.013413268591324624'],\n",
       "       dtype='<U32'), array(['C11', '0.012366386458128355'],\n",
       "       dtype='<U32'), array(['C10', '0.011022221770323784'],\n",
       "       dtype='<U32'), array(['I5', '0.01042866903792042'],\n",
       "       dtype='<U32'), array(['C16', '0.010389410428237439'],\n",
       "       dtype='<U32'), array(['I9', '0.009918639946598076'],\n",
       "       dtype='<U32'), array(['C2', '0.006787009911825981'],\n",
       "       dtype='<U32'), array(['C12', '0.005168884905437884'],\n",
       "       dtype='<U32'), array(['I4', '0.00468917800335175'],\n",
       "       dtype='<U32'), array(['C26', '0.003364625407413743'],\n",
       "       dtype='<U32'), array(['C23', '0.0031263193710805628'],\n",
       "       dtype='<U32'), array(['C21', '0.0008737398560005959'],\n",
       "       dtype='<U32'), array(['C19', '0.00042059860405565207'],\n",
       "       dtype='<U32'), array(['I2', '0.0'],\n",
       "       dtype='<U32'), array(['I10', '0.0'],\n",
       "       dtype='<U32'), array(['I12', '0.0'],\n",
       "       dtype='<U32'), array(['C1', '0.0'],\n",
       "       dtype='<U32'), array(['C3', '0.0'],\n",
       "       dtype='<U32'), array(['C5', '0.0'],\n",
       "       dtype='<U32'), array(['C6', '0.0'],\n",
       "       dtype='<U32'), array(['C8', '0.0'],\n",
       "       dtype='<U32'), array(['C9', '0.0'],\n",
       "       dtype='<U32'), array(['C20', '0.0'],\n",
       "       dtype='<U32'), array(['C22', '0.0'],\n",
       "       dtype='<U32'), array(['C25', '0.0'],\n",
       "       dtype='<U32')]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ret_feat_impt(gbm)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 保存GBDT参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "dump = gbm.dump_model()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "save_params_with_name((gbm, dump), 'gbm_dump') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "gbm, dump = load_params_with_name('gbm_dump') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 通过eli5分析参数\n",
    "超级慢，看看就好，谨慎运行代码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "import eli5 \n",
    "\n",
    "from sklearn.feature_extraction import DictVectorizer\n",
    "from sklearn.pipeline import make_pipeline\n",
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "from sklearn.utils import shuffle\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'C1': '2',\n",
       "  'C10': '7450',\n",
       "  'C11': '11013',\n",
       "  'C12': '11623',\n",
       "  'C13': '14481',\n",
       "  'C14': '14962',\n",
       "  'C15': '15302',\n",
       "  'C16': '16935',\n",
       "  'C17': '18436',\n",
       "  'C18': '18472',\n",
       "  'C19': '19603',\n",
       "  'C2': '152',\n",
       "  'C20': '20105',\n",
       "  'C21': '20107',\n",
       "  'C22': '21538',\n",
       "  'C23': '21549',\n",
       "  'C24': '22706',\n",
       "  'C25': '23114',\n",
       "  'C26': '24074',\n",
       "  'C3': '556',\n",
       "  'C4': '1896',\n",
       "  'C5': '3633',\n",
       "  'C6': '3684',\n",
       "  'C7': '6847',\n",
       "  'C8': '6887',\n",
       "  'C9': '6966',\n",
       "  'I1': '0.05',\n",
       "  'I10': '0.125',\n",
       "  'I11': '0.2',\n",
       "  'I12': '0',\n",
       "  'I13': '0.04',\n",
       "  'I2': '0.004983',\n",
       "  'I3': '0.05',\n",
       "  'I4': '0',\n",
       "  'I5': '0.021594',\n",
       "  'I6': '0.008',\n",
       "  'I7': '0.15',\n",
       "  'I8': '0.04',\n",
       "  'I9': '0.362',\n",
       "  'clicked': '0'}]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import csv\n",
    "import numpy as np\n",
    "\n",
    "with open('./data/train_eli5.csv', 'rt') as f:\n",
    "    data = list(csv.DictReader(f))\n",
    "data[:1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "899991 items total, 25.5% true\n"
     ]
    }
   ],
   "source": [
    "_all_xs = [{k: v for k, v in row.items() if k != 'clicked'} for row in data]\n",
    "_all_ys = np.array([int(row['clicked']) for row in data])\n",
    "\n",
    "all_xs, all_ys = shuffle(_all_xs, _all_ys, random_state=0)\n",
    "train_xs, valid_xs, train_ys, valid_ys = train_test_split(\n",
    "    all_xs, all_ys, test_size=0.25, random_state=0)\n",
    "print('{} items total, {:.1%} true'.format(len(all_xs), np.mean(all_ys)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.776 ± 0.003\n"
     ]
    }
   ],
   "source": [
    "# from xgboost import XGBClassifier\n",
    "import warnings\n",
    "# xgboost <= 0.6a2 shows a warning when used with scikit-learn 0.18+\n",
    "warnings.filterwarnings('ignore', category=UserWarning)\n",
    "class CSCTransformer:\n",
    "    def transform(self, xs):\n",
    "        # work around https://github.com/dmlc/xgboost/issues/1238#issuecomment-243872543\n",
    "        return xs.tocsc()\n",
    "    def fit(self, *args):\n",
    "        return self\n",
    "\n",
    "clf =  lgb.LGBMClassifier()\n",
    "vec = DictVectorizer()\n",
    "pipeline = make_pipeline(vec, CSCTransformer(), clf)\n",
    "\n",
    "def evaluate(_clf):\n",
    "    scores = cross_val_score(_clf, all_xs, all_ys, scoring='accuracy', cv=10)\n",
    "    print('Accuracy: {:.3f} ± {:.3f}'.format(np.mean(scores), 2 * np.std(scores)))\n",
    "    _clf.fit(train_xs, train_ys)  # so that parts of the original pipeline are fitted\n",
    "\n",
    "evaluate(pipeline)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "booster = clf.booster_   #如果运行出错请使用这句clf.booster()\n",
    "original_feature_names = booster.feature_name\n",
    "booster.feature_names = vec.get_feature_names()\n",
    "# recover original feature names\n",
    "booster.feature_names = original_feature_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <style>\n",
       "    table.eli5-weights tr:hover {\n",
       "        filter: brightness(85%);\n",
       "    }\n",
       "</style>\n",
       "\n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "        <table class=\"eli5-weights eli5-feature-importances\" style=\"border-collapse: collapse; border: none; margin-top: 0em; table-layout: auto;\">\n",
       "    <thead>\n",
       "    <tr style=\"border: none;\">\n",
       "        <th style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">Weight</th>\n",
       "        <th style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">Feature</th>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 80.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.1726\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                I1=0\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 90.56%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0591\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                I11=0\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 90.62%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0585\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                I11=0.1\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 91.81%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0482\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                I13=0\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 93.72%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0330\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                I6=0\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 94.58%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0268\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                I7=0\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 95.00%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0238\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                C17=18436\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 95.07%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0234\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                C14=14963\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.19%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0162\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                C14=14960\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.19%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0162\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                C14=14966\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.56%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0139\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                I4=0\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.57%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0139\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                I11=0.2\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.64%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0135\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                C23=21553\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.67%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0133\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                I6=0.002\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 96.80%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0126\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                I8=0\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 97.10%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0109\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                I6=0.004\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 97.36%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0096\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                I13=0.02\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 97.50%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0089\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                C7=3696\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 97.59%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0084\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                C14=14967\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "        <tr style=\"background-color: hsl(120, 100.00%, 97.60%); border: none;\">\n",
       "            <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "                0.0084\n",
       "                \n",
       "            </td>\n",
       "            <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "                C20=20104\n",
       "            </td>\n",
       "        </tr>\n",
       "    \n",
       "    \n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 97.60%); border: none;\">\n",
       "                <td colspan=\"2\" style=\"padding: 0 0.5em 0 0.5em; text-align: center; border: none; white-space: nowrap;\">\n",
       "                    <i>&hellip; 102771 more &hellip;</i>\n",
       "                </td>\n",
       "            </tr>\n",
       "        \n",
       "    \n",
       "    </tbody>\n",
       "</table>\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from eli5 import show_weights\n",
    "show_weights(clf, vec=vec)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <style>\n",
       "    table.eli5-weights tr:hover {\n",
       "        filter: brightness(85%);\n",
       "    }\n",
       "</style>\n",
       "\n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "        \n",
       "\n",
       "    \n",
       "\n",
       "        \n",
       "            \n",
       "                \n",
       "                \n",
       "    \n",
       "        <p style=\"margin-bottom: 0.5em; margin-top: 0em\">\n",
       "            <b>\n",
       "    \n",
       "        y=0\n",
       "    \n",
       "</b>\n",
       "\n",
       "    \n",
       "    (probability <b>0.931</b>, score <b>-2.597</b>)\n",
       "\n",
       "top features\n",
       "        </p>\n",
       "    \n",
       "    <table class=\"eli5-weights\"\n",
       "           style=\"border-collapse: collapse; border: none; margin-top: 0em; table-layout: auto; margin-bottom: 2em;\">\n",
       "        <thead>\n",
       "        <tr style=\"border: none;\">\n",
       "            \n",
       "                <th style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\" title=\"Feature contribution already accounts for the feature value (for linear models, contribution = weight * feature value), and the sum of feature contributions is equal to the score or, for some classifiers, to the probability. Feature values are shown if &quot;show_feature_values&quot; is True.\">\n",
       "                    Contribution<sup>?</sup>\n",
       "                </th>\n",
       "            \n",
       "            <th style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">Feature</th>\n",
       "            \n",
       "                <th style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">Value</th>\n",
       "            \n",
       "        </tr>\n",
       "        </thead>\n",
       "        <tbody>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 80.00%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +1.253\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        &lt;BIAS&gt;\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 93.10%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.274\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I11=0\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 94.38%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.205\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C9=6966\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 94.65%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.190\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I1=0\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 95.69%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.140\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I7=0\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 95.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.128\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C17=18436\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 97.01%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.083\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C20=20104\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 97.61%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.060\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I13=0\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 97.69%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.057\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C23=21548\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 97.80%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.054\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C25=23114\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 97.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.047\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21564\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 98.40%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.034\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I3=0\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 98.47%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.032\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C22=21538\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 98.60%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.028\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C9=6967\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 98.77%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.023\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C14=14963\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 98.79%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.023\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I3=0.01\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 98.79%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.023\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I8=0\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 98.79%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.023\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C23=21549\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 98.89%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.020\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C14=14961\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 98.89%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.020\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I8=0.02\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.00%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.017\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=137\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.14%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.014\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C23=21550\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.16%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.014\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I3=0.02\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.33%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.010\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C6=3688\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.35%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.009\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I4=0.02\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.44%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.008\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I13=0.06\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.44%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.008\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I8=0.04\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.52%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.006\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I3=0.04\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.52%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.006\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I3=0.03\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.53%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.006\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C20=20105\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.57%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.005\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I13=0.04\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.57%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.005\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C6=3685\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.58%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.005\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C7=3696\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.60%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.005\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C17=18442\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.60%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.005\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C19=19605\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.62%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I10=0\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.63%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11635\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.64%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18447\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.64%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.01\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.64%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.016\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.65%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.008\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.65%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.002\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.66%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13025\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.66%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.014\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.66%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.012\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.67%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.004\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.68%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I5=0.000016\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.68%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.018\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.68%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.006\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.68%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C20=20103\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.69%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I5=0.000031\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.69%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I3=0.05\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.70%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21567\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.70%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C14=14962\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.70%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C19=19607\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.72%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15158\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.72%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I3=0.06\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.73%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23157\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.73%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C19=19626\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.74%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=163\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.74%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C14=14965\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.74%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C14=14968\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.75%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I9=0.002\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.76%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I8=0.08\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.76%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13023\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.77%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I8=0.06\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.77%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23156\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.78%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I8=0.1\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.78%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.022\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.79%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.02\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.79%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9399\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.80%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13456\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.82%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=257\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.82%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I9=0.006\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.82%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=177\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.82%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I9=0.01\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.83%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.026\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.84%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C25=23125\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.84%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I9=0.004\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.84%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I9=0.008\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.84%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I9=0\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.84%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I10=0.25\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.84%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15304\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.85%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=7015\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.85%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.024\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.85%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.032\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.85%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=162\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.86%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9400\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.86%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C14=14979\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.86%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9719\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.86%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18456\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.87%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.028\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.87%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.036\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.87%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=150\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.87%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15025\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.88%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18594\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.88%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13060\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.89%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11644\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.89%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I9=0.014\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.89%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9412\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.89%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C19=19610\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=7002\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I5=0.000063\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15113\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23745\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18467\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18536\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C25=23122\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9417\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9382\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11815\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.034\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9436\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=186\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.91%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.04\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.91%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.03\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.91%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23169\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.91%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9418\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.92%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9457\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.92%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15072\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.92%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21617\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.92%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9434\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.92%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=14988\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.92%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23205\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.92%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I9=0.02\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=1976\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9386\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=6990\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13143\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13200\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15104\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11638\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9420\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21734\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=16098\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15139\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18460\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23184\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21598\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=19048\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21589\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9717\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=7001\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21584\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I11=1.2\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C16=17056\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13072\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18558\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=1977\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=180\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13338\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23196\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13140\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=317\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=7023\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I9=0.012\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I9=0.018\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9540\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18725\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C7=4425\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21641\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21627\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21699\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C16=17002\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9864\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9573\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23274\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13061\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13020\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=12236\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21565\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9493\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=7104\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=12076\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9685\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.042\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I11=1.3\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15029\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9519\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9515\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23266\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13397\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9524\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=2091\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21626\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11671\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23292\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0.044\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18545\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=19364\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=7239\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15195\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11911\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=12292\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13125\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=215\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11691\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C21=20183\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11741\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11692\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13100\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15028\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9472\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21732\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23312\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15396\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=2198\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I11=1\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9544\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11641\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15379\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11702\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=7043\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=12194\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9841\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11745\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I5=0.000125\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15203\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18631\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=6985\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C7=5513\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9559\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=12874\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15250\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18653\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18708\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21893\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11713\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15410\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=1950\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9756\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21662\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23283\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C19=19614\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18852\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11818\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21796\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15081\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I11=1.6\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=2559\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=10281\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C25=23130\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11791\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C25=23132\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15518\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C19=19632\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18610\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23446\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=3131\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21897\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=2680\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=248\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9530\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C7=3990\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=22034\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18801\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=7096\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23521\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C3=1144\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9624\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18739\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9702\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23254\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15270\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13305\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21784\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15439\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23238\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21964\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15352\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15421\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C16=17597\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15487\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18786\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C7=4186\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15367\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=2166\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=7319\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=2175\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18836\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15718\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=16516\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9858\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=16160\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=10217\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23429\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21848\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15569\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11898\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=422\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13781\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=22062\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=10499\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15872\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C21=20517\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=12324\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=12982\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15668\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=2425\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23516\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23580\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=12148\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=12135\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=2511\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=14745\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=12926\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C16=17799\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=8762\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=12377\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C16=18054\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=22934\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(120, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        +0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=19500\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "        \n",
       "\n",
       "        \n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=10546\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23481\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=12006\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C16=17265\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=10037\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23379\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15482\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11873\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=7241\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21741\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13460\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21725\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.99%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=7164\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11782\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9608\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13298\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21672\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13250\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C7=3881\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13148\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21656\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I13=0.82\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C19=19635\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9468\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9492\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9463\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15498\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13577\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15511\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C7=3863\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=229\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18604\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21755\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11950\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C19=19676\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15070\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.98%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I13=0.62\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15562\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23240\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18881\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=213\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13053\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13048\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23177\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23261\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18517\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9388\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13062\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=205\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13231\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=10060\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9907\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=6979\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C7=4057\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9512\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18662\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18491\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C7=3716\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9693\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21649\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=7016\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C7=4106\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.97%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9538\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18496\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15053\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9549\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11670\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=1920\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15003\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C7=3724\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=6973\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23250\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15476\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.96%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=14993\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13159\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11716\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21616\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18668\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23204\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=173\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13129\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13007\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23158\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9363\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21671\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9377\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11781\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21579\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21583\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15078\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9476\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9429\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11715\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I12=0.1\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21585\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13011\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.94%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18528\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11646\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15019\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=149\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11662\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C15=15305\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C19=19617\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.93%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=165\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.92%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13029\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.92%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21618\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.92%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=1927\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.92%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9381\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.92%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.000\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=169\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.92%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18488\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.91%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23163\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.91%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9349\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.91%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C17=18444\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.91%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=211\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.91%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C14=14978\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11647\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18532\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I2=0.303987\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I2=0.008306\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C26=23179\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21594\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C14=14975\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.90%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C12=11669\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.89%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C18=18461\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.89%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C17=18443\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.89%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C7=3693\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.88%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C11=9374\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.88%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I2=0.302326\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.86%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=6976\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.86%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=1908\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.86%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I1=0.05\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.85%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13016\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.84%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=155\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.84%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.001\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=156\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.81%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C7=3781\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.81%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=6974\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.80%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C16=16945\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.80%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C23=21556\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.80%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I7=0.01\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.79%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I2=0.006645\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.78%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I10=0.125\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.78%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.002\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C13=13010\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.73%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I2=0.004983\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.70%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=168\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.68%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.003\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C4=1897\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.67%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=6972\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.66%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=139\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.62%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.004\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I11=0.2\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.59%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.005\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I2=0.003322\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.58%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.005\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C14=14964\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.57%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.005\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21568\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.55%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.006\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C17=18438\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.54%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.006\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C2=141\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.51%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.006\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C24=21575\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.47%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.007\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C25=23113\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.45%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.007\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C17=18440\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.40%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.008\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C14=14967\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.34%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.010\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I11=0.1\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 99.02%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.017\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C14=14966\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 98.85%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.021\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C10=6970\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 98.74%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.024\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C6=3683\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 98.53%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.030\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C23=21553\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 97.95%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.048\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        C14=14960\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 97.76%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.055\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I13=0.02\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            1.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "            <tr style=\"background-color: hsl(0, 100.00%, 96.76%); border: none;\">\n",
       "    <td style=\"padding: 0 1em 0 0.5em; text-align: right; border: none;\">\n",
       "        -0.093\n",
       "    </td>\n",
       "    <td style=\"padding: 0 0.5em 0 0.5em; text-align: left; border: none;\">\n",
       "        I6=0\n",
       "    </td>\n",
       "    \n",
       "        <td style=\"padding: 0 0.5em 0 1em; text-align: right; border: none;\">\n",
       "            0.000\n",
       "        </td>\n",
       "    \n",
       "</tr>\n",
       "        \n",
       "\n",
       "        </tbody>\n",
       "    </table>\n",
       "\n",
       "            \n",
       "        \n",
       "\n",
       "        \n",
       "\n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "    \n",
       "\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from eli5 import show_prediction\n",
    "show_prediction(clf, valid_xs[1], vec=vec, show_feature_values=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 用LightGBM的输出生成FM数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据格式请参见[`libFM 1.4.2 manual`](http://www.libfm.org/libfm-1.42.manual.pdf)中的说明，截取文档中的格式说明如下：\n",
    "<img src=\"fm_format.png\"\\>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "GBDT已经训练好了，我们需要GBDT输出的叶子节点作为输入数据X传给FM，一共30个叶子节点，那么输入给FM的数据格式就是X中不是0的数据的index:value。\n",
    "\n",
    "一段真实数据如下：0\t0:31\t1:61\t2:93\t3:108\t4:149\t5:182\t6:212\t7:242\t8:277\t9:310\t10:334\t11:365\t12:401\t13:434\t14:465\t15:491\t16:527\t17:552\t18:589\t19:619\t20:648\t21:678\t22:697\t23:744\t24:770\t25:806\t26:826\t27:862\t28:899\t29:928\t30:955\t31:988"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generat_lgb2fm_data(outdir, gbm, dump, tr_path, va_path, te_path, _sep = '\\t'):\n",
    "    with open(os.path.join(outdir, 'train_lgb2fm.txt'), 'w') as out_train:\n",
    "        with open(os.path.join(outdir, 'valid_lgb2fm.txt'), 'w') as out_valid:\n",
    "            with open(os.path.join(outdir, 'test_lgb2fm.txt'), 'w') as out_test:\n",
    "                df_train_ = pd.read_csv(tr_path, header=None, sep=_sep)\n",
    "                df_valid_ = pd.read_csv(va_path, header=None, sep=_sep)\n",
    "                df_test_= pd.read_csv(te_path, header=None, sep=_sep)\n",
    "\n",
    "                y_train_ = df_train_[0].values\n",
    "                y_valid_ = df_valid_[0].values                \n",
    "\n",
    "                X_train_ = df_train_.drop(0, axis=1).values\n",
    "                X_valid_ = df_valid_.drop(0, axis=1).values\n",
    "                X_test_= df_test_.values\n",
    "   \n",
    "                train_leaves= gbm.predict(X_train_, num_iteration=gbm.best_iteration, pred_leaf=True)\n",
    "                valid_leaves= gbm.predict(X_valid_, num_iteration=gbm.best_iteration, pred_leaf=True)\n",
    "                test_leaves= gbm.predict(X_test_, num_iteration=gbm.best_iteration, pred_leaf=True)\n",
    "\n",
    "                tree_info = dump['tree_info']\n",
    "                tree_counts = len(tree_info)\n",
    "                for i in range(tree_counts):\n",
    "                    train_leaves[:, i] = train_leaves[:, i] + tree_info[i]['num_leaves'] * i + 1\n",
    "                    valid_leaves[:, i] = valid_leaves[:, i] + tree_info[i]['num_leaves'] * i + 1\n",
    "                    test_leaves[:, i] = test_leaves[:, i] + tree_info[i]['num_leaves'] * i + 1\n",
    "#                     print(train_leaves[:, i])\n",
    "#                     print(tree_info[i]['num_leaves'])\n",
    "\n",
    "                for idx in range(len(y_train_)):            \n",
    "                    out_train.write((str(y_train_[idx]) + '\\t'))\n",
    "                    out_train.write('\\t'.join(\n",
    "                        ['{}:{}'.format(ii, val) for ii,val in enumerate(train_leaves[idx]) if float(val) != 0 ]) + '\\n')\n",
    "                    \n",
    "                for idx in range(len(y_valid_)):                   \n",
    "                    out_valid.write((str(y_valid_[idx]) + '\\t'))\n",
    "                    out_valid.write('\\t'.join(\n",
    "                        ['{}:{}'.format(ii, val) for ii,val in enumerate(valid_leaves[idx]) if float(val) != 0 ]) + '\\n')\n",
    "                    \n",
    "                for idx in range(len(X_test_)):                   \n",
    "                    out_test.write('\\t'.join(\n",
    "                        ['{}:{}'.format(ii, val) for ii,val in enumerate(test_leaves[idx]) if float(val) != 0 ]) + '\\n')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "generat_lgb2fm_data('./data', gbm, dump, './data/train_lgb.txt', './data/valid_lgb.txt', './data/test_lgb.txt', '\\t')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 训练FM\n",
    "为训练FM的数据已经准备好了，我们调用LibFM进行训练。\n",
    "\n",
    "迭代64次，使用sgd训练，学习率是0.00000001，训练好的模型保存为文件fm_model。\n",
    "\n",
    "训练输出的log，Train和Test的数值不是loss，是accuracy。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['----------------------------------------------------------------------------\\n',\n",
       " 'libFM\\n',\n",
       " '  Version: 1.4.4\\n',\n",
       " '  Author:  Steffen Rendle, srendle@libfm.org\\n',\n",
       " '  WWW:     http://www.libfm.org/\\n',\n",
       " 'This program comes with ABSOLUTELY NO WARRANTY; for details see license.txt.\\n',\n",
       " 'This is free software, and you are welcome to redistribute it under certain\\n',\n",
       " 'conditions; for details see license.txt.\\n',\n",
       " '----------------------------------------------------------------------------\\n',\n",
       " 'Loading train...\\t\\n',\n",
       " 'has x = 1\\n',\n",
       " 'has xt = 0\\n',\n",
       " 'num_rows=899991\\tnum_values=28799712\\tnum_features=32\\tmin_target=0\\tmax_target=1\\n',\n",
       " 'Loading test... \\t\\n',\n",
       " 'has x = 1\\n',\n",
       " 'has xt = 0\\n',\n",
       " 'num_rows=100009\\tnum_values=3200288\\tnum_features=32\\tmin_target=0\\tmax_target=1\\n',\n",
       " '#relations: 0\\n',\n",
       " 'Loading meta data...\\t\\n',\n",
       " 'learnrate=1e-08\\n',\n",
       " 'learnrates=1e-08,1e-08,1e-08\\n',\n",
       " '#iterations=64\\n',\n",
       " \"SGD: DON'T FORGET TO SHUFFLE THE ROWS IN TRAINING DATA TO GET THE BEST RESULTS.\\n\",\n",
       " '#Iter=  0\\tTrain=0.625438\\tTest=0.619484\\n',\n",
       " '#Iter=  1\\tTrain=0.636596\\tTest=0.632013\\n',\n",
       " '#Iter=  2\\tTrain=0.627663\\tTest=0.623114\\n',\n",
       " '#Iter=  3\\tTrain=0.609776\\tTest=0.606605\\n',\n",
       " '#Iter=  4\\tTrain=0.563581\\tTest=0.56092\\n',\n",
       " '#Iter=  5\\tTrain=0.497907\\tTest=0.495655\\n',\n",
       " '#Iter=  6\\tTrain=0.461677\\tTest=0.461408\\n',\n",
       " '#Iter=  7\\tTrain=0.453666\\tTest=0.452639\\n',\n",
       " '#Iter=  8\\tTrain=0.454026\\tTest=0.453419\\n',\n",
       " '#Iter=  9\\tTrain=0.456836\\tTest=0.455919\\n',\n",
       " '#Iter= 10\\tTrain=0.46032\\tTest=0.459339\\n',\n",
       " '#Iter= 11\\tTrain=0.466546\\tTest=0.465358\\n',\n",
       " '#Iter= 12\\tTrain=0.473565\\tTest=0.472317\\n',\n",
       " '#Iter= 13\\tTrain=0.481726\\tTest=0.480967\\n',\n",
       " '#Iter= 14\\tTrain=0.492357\\tTest=0.491216\\n',\n",
       " '#Iter= 15\\tTrain=0.504419\\tTest=0.502935\\n',\n",
       " '#Iter= 16\\tTrain=0.517793\\tTest=0.516214\\n',\n",
       " '#Iter= 17\\tTrain=0.533604\\tTest=0.532102\\n',\n",
       " '#Iter= 18\\tTrain=0.552926\\tTest=0.5515\\n',\n",
       " '#Iter= 19\\tTrain=0.575645\\tTest=0.573198\\n',\n",
       " '#Iter= 20\\tTrain=0.59418\\tTest=0.590887\\n',\n",
       " '#Iter= 21\\tTrain=0.610691\\tTest=0.607815\\n',\n",
       " '#Iter= 22\\tTrain=0.626138\\tTest=0.623384\\n',\n",
       " '#Iter= 23\\tTrain=0.640751\\tTest=0.637923\\n',\n",
       " '#Iter= 24\\tTrain=0.65393\\tTest=0.652141\\n',\n",
       " '#Iter= 25\\tTrain=0.666099\\tTest=0.6641\\n',\n",
       " '#Iter= 26\\tTrain=0.677933\\tTest=0.675419\\n',\n",
       " '#Iter= 27\\tTrain=0.689539\\tTest=0.687108\\n',\n",
       " '#Iter= 28\\tTrain=0.700177\\tTest=0.697397\\n',\n",
       " '#Iter= 29\\tTrain=0.709265\\tTest=0.706156\\n',\n",
       " '#Iter= 30\\tTrain=0.716553\\tTest=0.713266\\n',\n",
       " '#Iter= 31\\tTrain=0.723218\\tTest=0.719635\\n',\n",
       " '#Iter= 32\\tTrain=0.729163\\tTest=0.726065\\n',\n",
       " '#Iter= 33\\tTrain=0.734428\\tTest=0.731354\\n',\n",
       " '#Iter= 34\\tTrain=0.738863\\tTest=0.735844\\n',\n",
       " '#Iter= 35\\tTrain=0.74284\\tTest=0.740323\\n',\n",
       " '#Iter= 36\\tTrain=0.746316\\tTest=0.743793\\n',\n",
       " '#Iter= 37\\tTrain=0.749123\\tTest=0.746333\\n',\n",
       " '#Iter= 38\\tTrain=0.751573\\tTest=0.748493\\n',\n",
       " '#Iter= 39\\tTrain=0.753264\\tTest=0.750292\\n',\n",
       " '#Iter= 40\\tTrain=0.754803\\tTest=0.751642\\n',\n",
       " '#Iter= 41\\tTrain=0.756011\\tTest=0.753062\\n',\n",
       " '#Iter= 42\\tTrain=0.756902\\tTest=0.753892\\n',\n",
       " '#Iter= 43\\tTrain=0.757642\\tTest=0.754872\\n',\n",
       " '#Iter= 44\\tTrain=0.758293\\tTest=0.755372\\n',\n",
       " '#Iter= 45\\tTrain=0.758855\\tTest=0.755782\\n',\n",
       " '#Iter= 46\\tTrain=0.759293\\tTest=0.756322\\n',\n",
       " '#Iter= 47\\tTrain=0.759695\\tTest=0.756652\\n',\n",
       " '#Iter= 48\\tTrain=0.760084\\tTest=0.756982\\n',\n",
       " '#Iter= 49\\tTrain=0.760343\\tTest=0.757252\\n',\n",
       " '#Iter= 50\\tTrain=0.76055\\tTest=0.757332\\n',\n",
       " '#Iter= 51\\tTrain=0.760706\\tTest=0.757582\\n',\n",
       " '#Iter= 52\\tTrain=0.760944\\tTest=0.757842\\n',\n",
       " '#Iter= 53\\tTrain=0.761035\\tTest=0.757952\\n',\n",
       " '#Iter= 54\\tTrain=0.761173\\tTest=0.758152\\n',\n",
       " '#Iter= 55\\tTrain=0.761291\\tTest=0.758382\\n',\n",
       " '#Iter= 56\\tTrain=0.76142\\tTest=0.758412\\n',\n",
       " '#Iter= 57\\tTrain=0.761541\\tTest=0.758452\\n',\n",
       " '#Iter= 58\\tTrain=0.761677\\tTest=0.758572\\n',\n",
       " '#Iter= 59\\tTrain=0.76175\\tTest=0.758692\\n',\n",
       " '#Iter= 60\\tTrain=0.761829\\tTest=0.758822\\n',\n",
       " '#Iter= 61\\tTrain=0.761855\\tTest=0.758862\\n',\n",
       " '#Iter= 62\\tTrain=0.761918\\tTest=0.759002\\n',\n",
       " '#Iter= 63\\tTrain=0.761988\\tTest=0.758972\\n',\n",
       " 'Final\\tTrain=0.761988\\tTest=0.758972\\n',\n",
       " 'Writing FM model to fm_model\\n']"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmd = './libfm/libfm/bin/libFM -task c -train ./data/train_lgb2fm.txt -test ./data/valid_lgb2fm.txt -dim ’1,1,8’ -iter 64 -method sgd -learn_rate 0.00000001 -regular ’0,0,0.01’ -init_stdev 0.1 -save_model fm_model'\n",
    "os.popen(cmd).readlines()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "FM模型训练好了，我们把训练、验证和测试数据输入给FM，得到FM层的输出，输出的文件名为*.fm.logits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['----------------------------------------------------------------------------\\n',\n",
       " 'libFM\\n',\n",
       " '  Version: 1.4.4\\n',\n",
       " '  Author:  Steffen Rendle, srendle@libfm.org\\n',\n",
       " '  WWW:     http://www.libfm.org/\\n',\n",
       " 'This program comes with ABSOLUTELY NO WARRANTY; for details see license.txt.\\n',\n",
       " 'This is free software, and you are welcome to redistribute it under certain\\n',\n",
       " 'conditions; for details see license.txt.\\n',\n",
       " '----------------------------------------------------------------------------\\n',\n",
       " 'Loading train...\\t\\n',\n",
       " 'has x = 1\\n',\n",
       " 'has xt = 0\\n',\n",
       " 'num_rows=899991\\tnum_values=28799712\\tnum_features=32\\tmin_target=0\\tmax_target=1\\n',\n",
       " 'Loading test... \\t\\n',\n",
       " 'has x = 1\\n',\n",
       " 'has xt = 0\\n',\n",
       " 'num_rows=100009\\tnum_values=3200288\\tnum_features=32\\tmin_target=0\\tmax_target=1\\n',\n",
       " '#relations: 0\\n',\n",
       " 'Loading meta data...\\t\\n',\n",
       " 'Reading FM model... \\t\\n',\n",
       " 'Final\\tTrain=0.761987\\tTest=0.758982\\n']"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmd = './libfm/libfm/bin/libFM -task c -train ./data/train_lgb2fm.txt -test ./data/valid_lgb2fm.txt -dim ’1,1,8’ -iter 32 -method sgd -learn_rate 0.00000001 -regular ’0,0,0.01’ -init_stdev 0.1 -load_model fm_model -train_off true -prefix tr'\n",
    "os.popen(cmd).readlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['----------------------------------------------------------------------------\\n',\n",
       " 'libFM\\n',\n",
       " '  Version: 1.4.4\\n',\n",
       " '  Author:  Steffen Rendle, srendle@libfm.org\\n',\n",
       " '  WWW:     http://www.libfm.org/\\n',\n",
       " 'This program comes with ABSOLUTELY NO WARRANTY; for details see license.txt.\\n',\n",
       " 'This is free software, and you are welcome to redistribute it under certain\\n',\n",
       " 'conditions; for details see license.txt.\\n',\n",
       " '----------------------------------------------------------------------------\\n',\n",
       " 'Loading train...\\t\\n',\n",
       " 'has x = 1\\n',\n",
       " 'has xt = 0\\n',\n",
       " 'num_rows=100009\\tnum_values=3200288\\tnum_features=32\\tmin_target=0\\tmax_target=1\\n',\n",
       " 'Loading test... \\t\\n',\n",
       " 'has x = 1\\n',\n",
       " 'has xt = 0\\n',\n",
       " 'num_rows=100009\\tnum_values=3200288\\tnum_features=32\\tmin_target=0\\tmax_target=1\\n',\n",
       " '#relations: 0\\n',\n",
       " 'Loading meta data...\\t\\n',\n",
       " 'Reading FM model... \\t\\n',\n",
       " 'Final\\tTrain=0.758982\\tTest=0.758982\\n']"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmd = './libfm/libfm/bin/libFM -task c -train ./data/valid_lgb2fm.txt -test ./data/valid_lgb2fm.txt -dim ’1,1,8’ -iter 32 -method sgd -learn_rate 0.00000001 -regular ’0,0,0.01’ -init_stdev 0.1 -load_model fm_model -train_off true -prefix va'\n",
    "os.popen(cmd).readlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['----------------------------------------------------------------------------\\n',\n",
       " 'libFM\\n',\n",
       " '  Version: 1.4.4\\n',\n",
       " '  Author:  Steffen Rendle, srendle@libfm.org\\n',\n",
       " '  WWW:     http://www.libfm.org/\\n',\n",
       " 'This program comes with ABSOLUTELY NO WARRANTY; for details see license.txt.\\n',\n",
       " 'This is free software, and you are welcome to redistribute it under certain\\n',\n",
       " 'conditions; for details see license.txt.\\n',\n",
       " '----------------------------------------------------------------------------\\n',\n",
       " 'Loading train...\\t\\n',\n",
       " 'has x = 1\\n',\n",
       " 'has xt = 0\\n',\n",
       " 'num_rows=1000000\\tnum_values=32000000\\tnum_features=32\\tmin_target=0\\tmax_target=1\\n',\n",
       " 'Loading test... \\t\\n',\n",
       " 'has x = 1\\n',\n",
       " 'has xt = 0\\n',\n",
       " 'num_rows=100009\\tnum_values=3200288\\tnum_features=32\\tmin_target=0\\tmax_target=1\\n',\n",
       " '#relations: 0\\n',\n",
       " 'Loading meta data...\\t\\n',\n",
       " 'Reading FM model... \\t\\n',\n",
       " 'Final\\tTest=0.758982\\n']"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmd = './libfm/libfm/bin/libFM -task c -train ./data/test_lgb2fm.txt -test ./data/valid_lgb2fm.txt -dim ’1,1,8’ -iter 32 -method sgd -learn_rate 0.00000001 -regular ’0,0,0.01’ -init_stdev 0.1 -load_model fm_model -train_off true -prefix te -test2predict true'\n",
    "os.popen(cmd).readlines()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 开始构建模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "embed_dim = 32\n",
    "sparse_max = 30000 # sparse_feature_dim = 117568\n",
    "sparse_dim = 26\n",
    "dense_dim = 13\n",
    "out_dim = 400"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 全数据迭代器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_batches(Xs, ys, batch_size):\n",
    "    for start in range(0, len(Xs), batch_size):\n",
    "        end = min(start + batch_size, len(Xs))\n",
    "        yield Xs[start:end], ys[start:end]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 下采样数据迭代器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_batches_downsample(Xs, ys, batch_size):\n",
    "    ind_0 = ys==0\n",
    "    ind_1 = ys==1\n",
    "    Xs_0 = Xs[ind_0]\n",
    "    ys_0 = ys[ind_0]\n",
    "    Xs_1 = Xs[ind_1]\n",
    "    ys_1 = ys[ind_1]\n",
    "    sampling_ind = np.random.permutation(Xs_0.shape[0])[:Xs_1.shape[0]]\n",
    "    Xs_0_sampling = Xs_0[sampling_ind]\n",
    "    ys_0_sampling = ys_0[sampling_ind]\n",
    "    Xs_downsampled = np.concatenate((Xs_0_sampling, Xs_1))\n",
    "    ys_downsampled = np.concatenate((ys_0_sampling, ys_1))\n",
    "    downsampled_ind = np.random.permutation(Xs_downsampled.shape[0])\n",
    "    Xs_downsampled = Xs_downsampled[downsampled_ind]\n",
    "    ys_downsampled = ys_downsampled[downsampled_ind]\n",
    "    for start in range(0, len(Xs_downsampled), batch_size):\n",
    "        end = min(start + batch_size, len(Xs_downsampled))\n",
    "        yield Xs_downsampled[start:end], ys_downsampled[start:end]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 构建计算图\n",
    "如前所述，将FFM和FM层的输出经过全连接层，再和数值特征、嵌入向量的三层全连接层的输出连接在一起，做Logistic回归。\n",
    "\n",
    "采用LogLoss损失，FtrlOptimizer优化损失。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import datetime\n",
    "from tensorflow import keras\n",
    "from tensorflow.python.ops import summary_ops_v2\n",
    "import time\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "import time\n",
    "import datetime\n",
    "from sklearn.metrics import log_loss\n",
    "# from sklearn.learning_curve import learning_curve\n",
    "from sklearn.model_selection import learning_curve\n",
    "from sklearn import metrics as sk_metrics\n",
    "\n",
    "MODEL_DIR = \"./models\"\n",
    "\n",
    "\n",
    "class ctr_network(object):\n",
    "    def __init__(self, batch_size=32):\n",
    "        self.batch_size = batch_size\n",
    "        self.best_loss = 9999\n",
    "\n",
    "        self.losses = {'train': [], 'test': []}\n",
    "        self.pred_lst = []\n",
    "        self.test_y_lst = []\n",
    "        \n",
    "        # 定义输入\n",
    "        dense_input = tf.keras.layers.Input(shape=(dense_dim,), name='dense_input')\n",
    "        sparse_input = tf.keras.layers.Input(shape=(sparse_dim,), name='sparse_input')\n",
    "        FFM_input = tf.keras.layers.Input(shape=(1,), name='FFM_input')\n",
    "        FM_input = tf.keras.layers.Input(shape=(1,), name='FM_input')\n",
    "\n",
    "        # 输入类别特征，从嵌入层获得嵌入向量\n",
    "        sparse_embed_layer = tf.keras.layers.Embedding(sparse_max, embed_dim, input_length=sparse_dim)(sparse_input)\n",
    "        sparse_embed_layer = tf.keras.layers.Reshape([sparse_dim * embed_dim])(sparse_embed_layer)\n",
    "\n",
    "        # 输入数值特征，和嵌入向量链接在一起经过三层全连接层\n",
    "        input_combine_layer = tf.keras.layers.concatenate([dense_input, sparse_embed_layer])  # (?, 845 = 832 + 13)\n",
    "        fc1_layer = tf.keras.layers.Dense(out_dim, name=\"fc1_layer\", activation='relu')(input_combine_layer)\n",
    "        fc2_layer = tf.keras.layers.Dense(out_dim, name=\"fc2_layer\", activation='relu')(fc1_layer)\n",
    "        fc3_layer = tf.keras.layers.Dense(out_dim, name=\"fc3_layer\", activation='relu')(fc2_layer)\n",
    "\n",
    "        ffm_fc_layer = tf.keras.layers.Dense(1, name=\"ffm_fc_layer\")(FFM_input)\n",
    "        fm_fc_layer = tf.keras.layers.Dense(1, name=\"fm_fc_layer\")(FM_input)\n",
    "        feature_combine_layer = tf.keras.layers.concatenate([ffm_fc_layer, fm_fc_layer, fc3_layer], 1)  # (?, 402)\n",
    "\n",
    "        logits_output = tf.keras.layers.Dense(1, name=\"logits_layer\", activation='sigmoid')(feature_combine_layer)\n",
    "\n",
    "        self.model = tf.keras.Model(inputs=[dense_input, sparse_input, FFM_input, FM_input], outputs=[logits_output])\n",
    "        self.model.summary()\n",
    "\n",
    "        self.optimizer = tf.compat.v1.train.FtrlOptimizer(0.01)  # tf.keras.optimizers.Adam(0.01)\n",
    "        self.ComputeLoss = tf.keras.losses.LogLoss()\n",
    "\n",
    "        if tf.io.gfile.exists(MODEL_DIR):\n",
    "            #             print('Removing existing model dir: {}'.format(MODEL_DIR))\n",
    "            #             tf.io.gfile.rmtree(MODEL_DIR)\n",
    "            pass\n",
    "        else:\n",
    "            tf.io.gfile.makedirs(MODEL_DIR)\n",
    "\n",
    "        train_dir = os.path.join(MODEL_DIR, 'summaries', 'train')\n",
    "        test_dir = os.path.join(MODEL_DIR, 'summaries', 'eval')\n",
    "\n",
    "#         self.train_summary_writer = summary_ops_v2.create_file_writer(train_dir, flush_millis=10000)\n",
    "#         self.test_summary_writer = summary_ops_v2.create_file_writer(test_dir, flush_millis=10000, name='test')\n",
    "\n",
    "        checkpoint_dir = os.path.join(MODEL_DIR, 'checkpoints')\n",
    "        self.checkpoint_prefix = os.path.join(checkpoint_dir, 'ckpt')\n",
    "        self.checkpoint = tf.train.Checkpoint(model=self.model, optimizer=self.optimizer)\n",
    "\n",
    "        # Restore variables on creation if a checkpoint exists.\n",
    "        self.checkpoint.restore(tf.train.latest_checkpoint(checkpoint_dir))\n",
    "\n",
    "    def compute_metrics(self, labels, pred):\n",
    "        correct_prediction = tf.equal(tf.keras.backend.cast(pred > 0.5, 'float32'), labels)\n",
    "        accuracy = tf.reduce_mean(tf.keras.backend.cast(correct_prediction, 'float32'), name=\"accuracy\")\n",
    "        return accuracy  \n",
    "\n",
    "    @tf.function\n",
    "    def train_step(self, x, y):\n",
    "        # Record the operations used to compute the loss, so that the gradient\n",
    "        # of the loss with respect to the variables can be computed.\n",
    "        metrics = 0\n",
    "        with tf.GradientTape() as tape:\n",
    "            pred = self.model([x[0],\n",
    "                               x[1],\n",
    "                               x[2],\n",
    "                               x[3]], training=True)\n",
    "            loss = self.ComputeLoss(y, pred)\n",
    "            metrics = self.compute_metrics(y, pred)\n",
    "        grads = tape.gradient(loss, self.model.trainable_variables)\n",
    "        self.optimizer.apply_gradients(zip(grads, self.model.trainable_variables))\n",
    "        return loss, metrics, pred\n",
    "\n",
    "    def training(self, train_dataset, test_dataset, downsample_flg=True, epochs=1, log_freq=50):\n",
    "\n",
    "        train_X, train_y = train_dataset\n",
    "\n",
    "        for epoch_i in range(epochs):\n",
    "            if downsample_flg:\n",
    "                train_batches = get_batches_downsample(train_X, train_y, self.batch_size)\n",
    "                batch_num = (len(train_y[train_y==1])*2 // self.batch_size)\n",
    "            else:\n",
    "                train_batches = get_batches(train_X, train_y, self.batch_size)\n",
    "                batch_num = len(train_X) // self.batch_size\n",
    "\n",
    "            train_start = time.time()\n",
    "#             with self.train_summary_writer.as_default():\n",
    "            if True:\n",
    "                start = time.time()\n",
    "                # Metrics are stateful. They accumulate values and return a cumulative\n",
    "                # result when you call .result(). Clear accumulated values with .reset_states()\n",
    "                avg_loss = tf.keras.metrics.Mean('loss', dtype=tf.float32)\n",
    "                avg_acc = tf.keras.metrics.Mean('acc', dtype=tf.float32)\n",
    "                avg_auc = tf.keras.metrics.Mean('auc', dtype=tf.float32)\n",
    "\n",
    "                # Datasets can be iterated over like any other Python iterable.\n",
    "                for batch_i in range(batch_num):\n",
    "                    x, y = next(train_batches)\n",
    "                    if len(x) < self.batch_size:\n",
    "                        break\n",
    "                    \n",
    "                    loss, metrics, pred = self.train_step([x.take([2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14], 1),\n",
    "                               x.take(\n",
    "                                   [15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
    "                                    36, 37, 38, 39, 40], 1),\n",
    "                               np.reshape(x.take(0, 1), [self.batch_size, 1]),\n",
    "                               np.reshape(x.take(1, 1), [self.batch_size, 1])], np.expand_dims(y, 1))\n",
    "                    avg_loss(loss)\n",
    "                    avg_acc(metrics)\n",
    "\n",
    "                    prediction = tf.reshape(pred, y.shape)\n",
    "                    self.losses['train'].append(loss)\n",
    "\n",
    "                    if (np.mean(y) != 0):\n",
    "                        auc = sk_metrics.roc_auc_score(y, prediction)\n",
    "                    else:\n",
    "                        auc = -1\n",
    "\n",
    "                    avg_auc(auc)\n",
    "                    if tf.equal((epoch_i * (batch_num) + batch_i) % log_freq, 0):\n",
    "#                         summary_ops_v2.scalar('loss', avg_loss.result(), step=self.optimizer.iterations)\n",
    "                        #                         summary_ops_v2.scalar('mae', self.ComputeMetrics.result(), step=self.optimizer.iterations)\n",
    "#                         summary_ops_v2.scalar('acc', avg_acc.result(), step=self.optimizer.iterations)\n",
    "\n",
    "                        rate = log_freq / (time.time() - start)\n",
    "                        \n",
    "                        print('Epoch {:>3} Batch {:>4}/{} Loss: {:0.6f} acc: {:0.6f} auc = {} ({} steps/sec)'.format(\n",
    "                            epoch_i, batch_i, batch_num, avg_loss.result(), (avg_acc.result()), avg_auc.result(), rate))\n",
    "\n",
    "                        avg_auc.reset_states()\n",
    "                        avg_loss.reset_states()\n",
    "                        \n",
    "                        avg_acc.reset_states()\n",
    "                        start = time.time()\n",
    "\n",
    "            train_end = time.time()\n",
    "            print('\\nTrain time for epoch #{} : {}'.format(epoch_i + 1, train_end - train_start))\n",
    "#             with self.test_summary_writer.as_default():\n",
    "            self.testing(test_dataset)\n",
    "            # self.checkpoint.save(self.checkpoint_prefix)\n",
    "        self.export_path = os.path.join(MODEL_DIR, 'export')\n",
    "        tf.saved_model.save(self.model, self.export_path)\n",
    "\n",
    "    def testing(self, test_dataset):\n",
    "        test_X, test_y = test_dataset\n",
    "        test_batches = get_batches(test_X, test_y, self.batch_size)\n",
    "\n",
    "        \"\"\"Perform an evaluation of `model` on the examples from `dataset`.\"\"\"\n",
    "        avg_loss = tf.keras.metrics.Mean('loss', dtype=tf.float32)\n",
    "        avg_acc = tf.keras.metrics.Mean('acc', dtype=tf.float32)\n",
    "        avg_auc = tf.keras.metrics.Mean('auc', dtype=tf.float32)\n",
    "        avg_prediction = tf.keras.metrics.Mean('prediction', dtype=tf.float32)\n",
    "\n",
    "        self.pred_lst=[]\n",
    "        self.test_y_lst=[]\n",
    "        \n",
    "        batch_num = (len(test_X) // self.batch_size)\n",
    "        for batch_i in range(batch_num):\n",
    "            x, y = next(test_batches)\n",
    "            if len(x) < self.batch_size:\n",
    "                break\n",
    "            \n",
    "            pred = self.model([x.take([2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14], 1),\n",
    "                               x.take(\n",
    "                                   [15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
    "                                    36, 37, 38, 39, 40], 1),\n",
    "                               np.reshape(x.take(0, 1), [self.batch_size, 1]),\n",
    "                               np.reshape(x.take(1, 1), [self.batch_size, 1])], training=False)\n",
    "            test_loss = self.ComputeLoss(np.expand_dims(y, 1), pred)\n",
    "            avg_loss(test_loss)\n",
    "            acc = self.compute_metrics(np.expand_dims(y, 1), pred)\n",
    "            avg_acc(acc)\n",
    "\n",
    "            # 保存测试损失和准确率\n",
    "            prediction = tf.reshape(pred, y.shape)\n",
    "            avg_prediction(prediction)\n",
    "            self.losses['test'].append(test_loss)\n",
    "\n",
    "            self.pred_lst.append(prediction)\n",
    "            self.test_y_lst.append(y)\n",
    "\n",
    "            if (np.mean(y) != 0):\n",
    "                auc = sk_metrics.roc_auc_score(y, prediction)\n",
    "            else:\n",
    "                auc = -1\n",
    "            avg_auc(auc)\n",
    "\n",
    "        self.pred_lst = np.concatenate([val for val in self.pred_lst])\n",
    "        self.test_y_lst = np.concatenate([val for val in self.test_y_lst])\n",
    "        print('Model test set loss: {:0.6f}  acc: {:0.6f}  auc = {} prediction = {}'.format(\n",
    "            avg_loss.result(), avg_acc.result(), avg_auc.result(), avg_prediction.result()))\n",
    "        print(sk_metrics.classification_report(self.test_y_lst, tf.keras.backend.cast((self.pred_lst) > 0.5, 'float32')))\n",
    "#         summary_ops_v2.scalar('loss', avg_loss.result(), step=step_num)\n",
    "        #         summary_ops_v2.scalar('mae', self.ComputeMetrics.result(), step=step_num)\n",
    "#         summary_ops_v2.scalar('acc', avg_acc.result(), step=step_num)\n",
    "\n",
    "        if avg_loss.result() < self.best_loss:\n",
    "            self.best_loss = avg_loss.result()\n",
    "            print(\"best loss = {}\".format(self.best_loss))\n",
    "            self.checkpoint.save(self.checkpoint_prefix)\n",
    "\n",
    "    def predict_click(self, x, axis = 0):\n",
    "        clicked = self.model([np.reshape(x.take([2,3,4,5,6,7,8,9,10,11,12,13,14],axis), [1 if axis == 0 else len(x.take([2,3,4,5,6,7,8,9,10,11,12,13,14],axis)), 13]),\n",
    "                               np.reshape(x.take([15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40],axis), [1 if axis == 0 else len(x.take([15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40],axis)), 26]),\n",
    "                               np.reshape(x.take(0,axis), [1 if axis == 0 else len(x.take(0,axis)), 1]),\n",
    "                               np.reshape(x.take(1,axis), [1 if axis == 0 else len(x.take(0,axis)), 1])])\n",
    "\n",
    "        return (np.int32(np.array(clicked) > 0.5))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 超参\n",
    "数据量太大，我们只跑一个epoch。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Number of Epochs\n",
    "num_epochs = 1\n",
    "# Batch Size\n",
    "batch_size = 32\n",
    "\n",
    "# Learning Rate\n",
    "learning_rate = 0.01\n",
    "# Show stats for every n number of batches\n",
    "show_every_n_batches = 25\n",
    "\n",
    "save_dir = './save'\n",
    "\n",
    "ffm_tr_out_path = './tr_ffm.out.logit'\n",
    "ffm_va_out_path = './va_ffm.out.logit'\n",
    "fm_tr_out_path = './tr.fm.logits'\n",
    "fm_va_out_path = './va.fm.logits'\n",
    "train_path = './data/train.txt'\n",
    "valid_path = './data/valid.txt'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 读取FFM的输出"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "ffm_train = pd.read_csv(ffm_tr_out_path, header=None)    \n",
    "ffm_train = ffm_train[0].values\n",
    "\n",
    "ffm_valid = pd.read_csv(ffm_va_out_path, header=None)    \n",
    "ffm_valid = ffm_valid[0].values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 读取FM的输出"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "fm_train = pd.read_csv(fm_tr_out_path, header=None)    \n",
    "fm_train = fm_train[0].values\n",
    "\n",
    "fm_valid = pd.read_csv(fm_va_out_path, header=None)    \n",
    "fm_valid = fm_valid[0].values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 读取数据集\n",
    "\n",
    "将DNN数据和FM、FFM的输出数据读取出来，并连接在一起"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_data = pd.read_csv(train_path, header=None)    \n",
    "train_data = train_data.values\n",
    "\n",
    "valid_data = pd.read_csv(valid_path, header=None)    \n",
    "valid_data = valid_data.values\n",
    "\n",
    "cc_train = np.concatenate((ffm_train.reshape(-1, 1), fm_train.reshape(-1, 1), train_data), 1)\n",
    "cc_valid = np.concatenate((ffm_valid.reshape(-1, 1), fm_valid.reshape(-1, 1), valid_data), 1)\n",
    "\n",
    "np.random.shuffle(cc_train)\n",
    "np.random.shuffle(cc_valid)\n",
    "\n",
    "train_y = cc_train[:,-1].astype(np.float32)\n",
    "test_y = cc_valid[:,-1].astype(np.float32)\n",
    "\n",
    "train_X = cc_train[:,0:-1].astype(np.float32)\n",
    "test_X = cc_valid[:,0:-1].astype(np.float32)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "来看训练数据和验证数据的平均点击率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.25485810413659693"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(train_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.25576698097171252"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(test_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 训练网络"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 输出验证集上的训练信息\n",
    " - 平均准确率\n",
    " - 平均损失\n",
    " - 平均Auc\n",
    " - 预测的平均点击率\n",
    " - 精确率、召回率、F1 Score等信息\n",
    " \n",
    "因为数据中大部分都是负例，正例较少，如果模型全部猜0就能有75%的准确率，所以准确率这个指标是不可信的。\n",
    "\n",
    "我们需要关注正例的精确率和召回率，当然最主要还是要看LogLoss的值，因为比赛采用的评价指标是LogLoss，而不是采用AUC值。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 下采样的训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_6\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "sparse_input (InputLayer)       [(None, 26)]         0                                            \n",
      "__________________________________________________________________________________________________\n",
      "embedding_6 (Embedding)         (None, 26, 32)       960000      sparse_input[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "dense_input (InputLayer)        [(None, 13)]         0                                            \n",
      "__________________________________________________________________________________________________\n",
      "reshape_6 (Reshape)             (None, 832)          0           embedding_6[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_12 (Concatenate)    (None, 845)          0           dense_input[0][0]                \n",
      "                                                                 reshape_6[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "fc1_layer (Dense)               (None, 400)          338400      concatenate_12[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "FFM_input (InputLayer)          [(None, 1)]          0                                            \n",
      "__________________________________________________________________________________________________\n",
      "FM_input (InputLayer)           [(None, 1)]          0                                            \n",
      "__________________________________________________________________________________________________\n",
      "fc2_layer (Dense)               (None, 400)          160400      fc1_layer[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "ffm_fc_layer (Dense)            (None, 1)            2           FFM_input[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "fm_fc_layer (Dense)             (None, 1)            2           FM_input[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "fc3_layer (Dense)               (None, 400)          160400      fc2_layer[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_13 (Concatenate)    (None, 402)          0           ffm_fc_layer[0][0]               \n",
      "                                                                 fm_fc_layer[0][0]                \n",
      "                                                                 fc3_layer[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "logits_layer (Dense)            (None, 1)            403         concatenate_13[0][0]             \n",
      "==================================================================================================\n",
      "Total params: 1,619,607\n",
      "Trainable params: 1,619,607\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "Epoch   0 Batch    0/14335 Loss: 0.686196 acc: 0.718750 auc = 0.8097165822982788 (20.28710214961916 steps/sec)\n",
      "Epoch   0 Batch   50/14335 Loss: 0.693178 acc: 0.500000 auc = 0.7953975200653076 (63.78323665667458 steps/sec)\n",
      "Epoch   0 Batch  100/14335 Loss: 0.693057 acc: 0.513125 auc = 0.7834470868110657 (67.1895129161435 steps/sec)\n",
      "Epoch   0 Batch  150/14335 Loss: 0.693114 acc: 0.506875 auc = 0.8074575662612915 (68.34981225533795 steps/sec)\n",
      "Epoch   0 Batch  200/14335 Loss: 0.692778 acc: 0.522500 auc = 0.8019921779632568 (69.55098261417788 steps/sec)\n",
      "Epoch   0 Batch  250/14335 Loss: 0.693255 acc: 0.496875 auc = 0.8014236688613892 (70.00900670528846 steps/sec)\n",
      "Epoch   0 Batch  300/14335 Loss: 0.693106 acc: 0.498750 auc = 0.7934594750404358 (69.50372896769753 steps/sec)\n",
      "Epoch   0 Batch  350/14335 Loss: 0.692703 acc: 0.511875 auc = 0.7842004299163818 (68.41021231398958 steps/sec)\n",
      "Epoch   0 Batch  400/14335 Loss: 0.692225 acc: 0.510000 auc = 0.8027440905570984 (69.77287033500528 steps/sec)\n",
      "Epoch   0 Batch  450/14335 Loss: 0.690975 acc: 0.531875 auc = 0.8046291470527649 (68.33709480538863 steps/sec)\n",
      "Epoch   0 Batch  500/14335 Loss: 0.689012 acc: 0.661250 auc = 0.8116732835769653 (66.78940759191158 steps/sec)\n",
      "Epoch   0 Batch  550/14335 Loss: 0.685877 acc: 0.728125 auc = 0.7963970899581909 (65.95219959959822 steps/sec)\n",
      "Epoch   0 Batch  600/14335 Loss: 0.681972 acc: 0.695625 auc = 0.7739514708518982 (65.56396712972878 steps/sec)\n",
      "Epoch   0 Batch  650/14335 Loss: 0.676774 acc: 0.686875 auc = 0.7964885234832764 (66.96272454994221 steps/sec)\n",
      "Epoch   0 Batch  700/14335 Loss: 0.670160 acc: 0.675625 auc = 0.8029649257659912 (65.01129787803252 steps/sec)\n",
      "Epoch   0 Batch  750/14335 Loss: 0.665943 acc: 0.673125 auc = 0.7898890972137451 (65.81156536384694 steps/sec)\n",
      "Epoch   0 Batch  800/14335 Loss: 0.658693 acc: 0.664375 auc = 0.7922184467315674 (66.98265795518715 steps/sec)\n",
      "Epoch   0 Batch  850/14335 Loss: 0.651819 acc: 0.688125 auc = 0.7977541089057922 (66.25963807229708 steps/sec)\n",
      "Epoch   0 Batch  900/14335 Loss: 0.652727 acc: 0.676875 auc = 0.7818065881729126 (67.60466035391714 steps/sec)\n",
      "Epoch   0 Batch  950/14335 Loss: 0.644341 acc: 0.686250 auc = 0.8023520112037659 (67.22804587973559 steps/sec)\n",
      "Epoch   0 Batch 1000/14335 Loss: 0.641845 acc: 0.676875 auc = 0.7902230620384216 (71.05612857889234 steps/sec)\n",
      "Epoch   0 Batch 1050/14335 Loss: 0.630059 acc: 0.693125 auc = 0.8016648292541504 (67.2223783970564 steps/sec)\n",
      "Epoch   0 Batch 1100/14335 Loss: 0.631589 acc: 0.695000 auc = 0.7917559742927551 (65.75857221740209 steps/sec)\n",
      "Epoch   0 Batch 1150/14335 Loss: 0.622978 acc: 0.676250 auc = 0.8013649582862854 (67.49880187850002 steps/sec)\n",
      "Epoch   0 Batch 1200/14335 Loss: 0.617526 acc: 0.698750 auc = 0.8015296459197998 (67.90673005032247 steps/sec)\n",
      "Epoch   0 Batch 1250/14335 Loss: 0.612302 acc: 0.698750 auc = 0.8032695055007935 (66.69013531360378 steps/sec)\n",
      "Epoch   0 Batch 1300/14335 Loss: 0.616461 acc: 0.698125 auc = 0.7849545478820801 (66.81517655514831 steps/sec)\n",
      "Epoch   0 Batch 1350/14335 Loss: 0.609482 acc: 0.683750 auc = 0.8042651414871216 (64.74681723146992 steps/sec)\n",
      "Epoch   0 Batch 1400/14335 Loss: 0.597565 acc: 0.708750 auc = 0.8143470287322998 (65.74857335623237 steps/sec)\n",
      "Epoch   0 Batch 1450/14335 Loss: 0.610107 acc: 0.695625 auc = 0.7922111749649048 (64.85901377527873 steps/sec)\n",
      "Epoch   0 Batch 1500/14335 Loss: 0.595128 acc: 0.713125 auc = 0.8057980537414551 (67.05416925522191 steps/sec)\n",
      "Epoch   0 Batch 1550/14335 Loss: 0.597356 acc: 0.710000 auc = 0.8108881115913391 (65.88440496902683 steps/sec)\n",
      "Epoch   0 Batch 1600/14335 Loss: 0.598662 acc: 0.698125 auc = 0.7851647734642029 (67.20611393510866 steps/sec)\n",
      "Epoch   0 Batch 1650/14335 Loss: 0.584198 acc: 0.716875 auc = 0.8104912042617798 (66.84750629379278 steps/sec)\n",
      "Epoch   0 Batch 1700/14335 Loss: 0.589507 acc: 0.705625 auc = 0.8077947497367859 (64.17991843589849 steps/sec)\n",
      "Epoch   0 Batch 1750/14335 Loss: 0.587692 acc: 0.708750 auc = 0.7993537187576294 (58.30121948303883 steps/sec)\n",
      "Epoch   0 Batch 1800/14335 Loss: 0.590012 acc: 0.696250 auc = 0.7856223583221436 (60.9868214617339 steps/sec)\n",
      "Epoch   0 Batch 1850/14335 Loss: 0.585396 acc: 0.702500 auc = 0.7919818758964539 (52.89409614022149 steps/sec)\n",
      "Epoch   0 Batch 1900/14335 Loss: 0.574120 acc: 0.719375 auc = 0.8197274804115295 (62.63505732021427 steps/sec)\n",
      "Epoch   0 Batch 1950/14335 Loss: 0.581953 acc: 0.713750 auc = 0.8010642528533936 (64.10256645383222 steps/sec)\n",
      "Epoch   0 Batch 2000/14335 Loss: 0.582166 acc: 0.712500 auc = 0.7888954281806946 (64.30537596293924 steps/sec)\n",
      "Epoch   0 Batch 2050/14335 Loss: 0.566999 acc: 0.721875 auc = 0.8145179748535156 (63.6389816194689 steps/sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch   0 Batch 2100/14335 Loss: 0.576945 acc: 0.712500 auc = 0.7928829193115234 (65.03684223583993 steps/sec)\n",
      "Epoch   0 Batch 2150/14335 Loss: 0.574854 acc: 0.718125 auc = 0.7858287692070007 (64.74839645870158 steps/sec)\n",
      "Epoch   0 Batch 2200/14335 Loss: 0.582252 acc: 0.702500 auc = 0.7833107113838196 (65.27918759604792 steps/sec)\n",
      "Epoch   0 Batch 2250/14335 Loss: 0.575599 acc: 0.711875 auc = 0.8042446374893188 (63.85517222900209 steps/sec)\n",
      "Epoch   0 Batch 2300/14335 Loss: 0.581700 acc: 0.708750 auc = 0.7794141173362732 (64.88492037709112 steps/sec)\n",
      "Epoch   0 Batch 2350/14335 Loss: 0.571279 acc: 0.697500 auc = 0.7989742159843445 (65.24159729221886 steps/sec)\n",
      "Epoch   0 Batch 2400/14335 Loss: 0.560575 acc: 0.719375 auc = 0.8070520162582397 (64.97969260667114 steps/sec)\n",
      "Epoch   0 Batch 2450/14335 Loss: 0.580612 acc: 0.705625 auc = 0.7793541550636292 (64.36002172798891 steps/sec)\n",
      "Epoch   0 Batch 2500/14335 Loss: 0.559743 acc: 0.717500 auc = 0.7985990643501282 (64.67393684309211 steps/sec)\n",
      "Epoch   0 Batch 2550/14335 Loss: 0.559917 acc: 0.719375 auc = 0.805484414100647 (55.120977439360146 steps/sec)\n",
      "Epoch   0 Batch 2600/14335 Loss: 0.576964 acc: 0.707500 auc = 0.7805522680282593 (62.969973576747535 steps/sec)\n",
      "Epoch   0 Batch 2650/14335 Loss: 0.547260 acc: 0.744375 auc = 0.829006016254425 (63.98207533411965 steps/sec)\n",
      "Epoch   0 Batch 2700/14335 Loss: 0.551755 acc: 0.733125 auc = 0.8125675320625305 (57.98916342108501 steps/sec)\n",
      "Epoch   0 Batch 2750/14335 Loss: 0.548469 acc: 0.725625 auc = 0.8132531642913818 (59.26557275869017 steps/sec)\n",
      "Epoch   0 Batch 2800/14335 Loss: 0.560907 acc: 0.717500 auc = 0.800249457359314 (50.81847681141896 steps/sec)\n",
      "Epoch   0 Batch 2850/14335 Loss: 0.539323 acc: 0.738125 auc = 0.8241413235664368 (60.2362975945716 steps/sec)\n",
      "Epoch   0 Batch 2900/14335 Loss: 0.544394 acc: 0.728125 auc = 0.817625880241394 (59.38632350259333 steps/sec)\n",
      "Epoch   0 Batch 2950/14335 Loss: 0.548983 acc: 0.730625 auc = 0.8153151869773865 (61.23039353369822 steps/sec)\n",
      "Epoch   0 Batch 3000/14335 Loss: 0.556239 acc: 0.718750 auc = 0.8021328449249268 (38.02596965540851 steps/sec)\n",
      "Epoch   0 Batch 3050/14335 Loss: 0.548238 acc: 0.722500 auc = 0.8074700832366943 (61.01214044867002 steps/sec)\n",
      "Epoch   0 Batch 3100/14335 Loss: 0.560659 acc: 0.706250 auc = 0.7889134883880615 (57.97920751457807 steps/sec)\n",
      "Epoch   0 Batch 3150/14335 Loss: 0.547720 acc: 0.719375 auc = 0.8085194230079651 (58.86896135113141 steps/sec)\n",
      "Epoch   0 Batch 3200/14335 Loss: 0.569577 acc: 0.706875 auc = 0.7827075123786926 (58.88582173181404 steps/sec)\n",
      "Epoch   0 Batch 3250/14335 Loss: 0.556170 acc: 0.722500 auc = 0.7959104180335999 (59.82313375762747 steps/sec)\n",
      "Epoch   0 Batch 3300/14335 Loss: 0.552251 acc: 0.723750 auc = 0.8056888580322266 (59.670705315230265 steps/sec)\n",
      "Epoch   0 Batch 3350/14335 Loss: 0.554167 acc: 0.719375 auc = 0.7984248399734497 (58.1979318892116 steps/sec)\n",
      "Epoch   0 Batch 3400/14335 Loss: 0.552918 acc: 0.721875 auc = 0.7958561778068542 (60.35164298820566 steps/sec)\n",
      "Epoch   0 Batch 3450/14335 Loss: 0.557060 acc: 0.700625 auc = 0.7983629703521729 (59.22849811143414 steps/sec)\n",
      "Epoch   0 Batch 3500/14335 Loss: 0.561383 acc: 0.707500 auc = 0.7879179120063782 (62.86411783185172 steps/sec)\n",
      "Epoch   0 Batch 3550/14335 Loss: 0.534356 acc: 0.730625 auc = 0.8209925293922424 (60.18165680116785 steps/sec)\n",
      "Epoch   0 Batch 3600/14335 Loss: 0.549573 acc: 0.723125 auc = 0.7942716479301453 (64.49741029527955 steps/sec)\n",
      "Epoch   0 Batch 3650/14335 Loss: 0.549794 acc: 0.726875 auc = 0.7996088266372681 (63.92290548020698 steps/sec)\n",
      "Epoch   0 Batch 3700/14335 Loss: 0.558447 acc: 0.710000 auc = 0.7917068600654602 (63.77090116926131 steps/sec)\n",
      "Epoch   0 Batch 3750/14335 Loss: 0.549745 acc: 0.722500 auc = 0.7973204851150513 (49.357702079486735 steps/sec)\n",
      "Epoch   0 Batch 3800/14335 Loss: 0.544312 acc: 0.721875 auc = 0.8085019588470459 (55.28656241102593 steps/sec)\n",
      "Epoch   0 Batch 3850/14335 Loss: 0.563650 acc: 0.713125 auc = 0.7784467339515686 (56.18684294356994 steps/sec)\n",
      "Epoch   0 Batch 3900/14335 Loss: 0.548006 acc: 0.723750 auc = 0.8001449704170227 (50.156137630711605 steps/sec)\n",
      "Epoch   0 Batch 3950/14335 Loss: 0.552965 acc: 0.713125 auc = 0.7927001714706421 (59.13800688060459 steps/sec)\n",
      "Epoch   0 Batch 4000/14335 Loss: 0.544631 acc: 0.729375 auc = 0.8019278645515442 (59.82929488711997 steps/sec)\n",
      "Epoch   0 Batch 4050/14335 Loss: 0.540775 acc: 0.723750 auc = 0.8039243221282959 (64.00976711534352 steps/sec)\n",
      "Epoch   0 Batch 4100/14335 Loss: 0.551941 acc: 0.708750 auc = 0.7943409085273743 (64.70045428952666 steps/sec)\n",
      "Epoch   0 Batch 4150/14335 Loss: 0.537463 acc: 0.733125 auc = 0.8121495246887207 (62.59568506116143 steps/sec)\n",
      "Epoch   0 Batch 4200/14335 Loss: 0.547627 acc: 0.726250 auc = 0.802532970905304 (61.46400937866354 steps/sec)\n",
      "Epoch   0 Batch 4250/14335 Loss: 0.565441 acc: 0.704375 auc = 0.7831739187240601 (65.15326528722834 steps/sec)\n",
      "Epoch   0 Batch 4300/14335 Loss: 0.547443 acc: 0.724375 auc = 0.7955663204193115 (63.17813285244712 steps/sec)\n",
      "Epoch   0 Batch 4350/14335 Loss: 0.543141 acc: 0.724375 auc = 0.8028111457824707 (63.28667297978655 steps/sec)\n",
      "Epoch   0 Batch 4400/14335 Loss: 0.536231 acc: 0.735625 auc = 0.806367814540863 (60.997180720936164 steps/sec)\n",
      "Epoch   0 Batch 4450/14335 Loss: 0.547755 acc: 0.716875 auc = 0.7982569932937622 (61.1632839240592 steps/sec)\n",
      "Epoch   0 Batch 4500/14335 Loss: 0.550645 acc: 0.720625 auc = 0.7990764379501343 (64.97431733114641 steps/sec)\n",
      "Epoch   0 Batch 4550/14335 Loss: 0.550879 acc: 0.728125 auc = 0.7995180487632751 (64.82635400599067 steps/sec)\n",
      "Epoch   0 Batch 4600/14335 Loss: 0.548255 acc: 0.722500 auc = 0.7985478043556213 (64.60774817805184 steps/sec)\n",
      "Epoch   0 Batch 4650/14335 Loss: 0.561463 acc: 0.716250 auc = 0.7827955484390259 (64.95397181629363 steps/sec)\n",
      "Epoch   0 Batch 4700/14335 Loss: 0.542596 acc: 0.729375 auc = 0.8002133369445801 (64.73816283508523 steps/sec)\n",
      "Epoch   0 Batch 4750/14335 Loss: 0.550427 acc: 0.728750 auc = 0.8016986846923828 (64.6124259452618 steps/sec)\n",
      "Epoch   0 Batch 4800/14335 Loss: 0.559645 acc: 0.716875 auc = 0.785897433757782 (60.22022868244991 steps/sec)\n",
      "Epoch   0 Batch 4850/14335 Loss: 0.548863 acc: 0.719375 auc = 0.7968437075614929 (58.14075085680003 steps/sec)\n",
      "Epoch   0 Batch 4900/14335 Loss: 0.531699 acc: 0.745000 auc = 0.8119109272956848 (63.2160880970051 steps/sec)\n",
      "Epoch   0 Batch 4950/14335 Loss: 0.528603 acc: 0.746250 auc = 0.8162219524383545 (49.56437560503388 steps/sec)\n",
      "Epoch   0 Batch 5000/14335 Loss: 0.531402 acc: 0.733750 auc = 0.8168033361434937 (56.48256802801246 steps/sec)\n",
      "Epoch   0 Batch 5050/14335 Loss: 0.540259 acc: 0.724375 auc = 0.8127132654190063 (64.11038537423138 steps/sec)\n",
      "Epoch   0 Batch 5100/14335 Loss: 0.543355 acc: 0.718750 auc = 0.8045293688774109 (63.2134394631256 steps/sec)\n",
      "Epoch   0 Batch 5150/14335 Loss: 0.541581 acc: 0.719375 auc = 0.8014801740646362 (55.527424640951324 steps/sec)\n",
      "Epoch   0 Batch 5200/14335 Loss: 0.550146 acc: 0.721250 auc = 0.79720139503479 (57.342664991080674 steps/sec)\n",
      "Epoch   0 Batch 5250/14335 Loss: 0.553027 acc: 0.714375 auc = 0.7908018231391907 (59.155071806005736 steps/sec)\n",
      "Epoch   0 Batch 5300/14335 Loss: 0.556281 acc: 0.702500 auc = 0.787492036819458 (59.72204067696021 steps/sec)\n",
      "Epoch   0 Batch 5350/14335 Loss: 0.557817 acc: 0.708750 auc = 0.7816433906555176 (62.51397668877599 steps/sec)\n",
      "Epoch   0 Batch 5400/14335 Loss: 0.555314 acc: 0.731875 auc = 0.7838160991668701 (56.99166682972113 steps/sec)\n",
      "Epoch   0 Batch 5450/14335 Loss: 0.550934 acc: 0.721250 auc = 0.7942750453948975 (59.109620527956935 steps/sec)\n",
      "Epoch   0 Batch 5500/14335 Loss: 0.536110 acc: 0.720625 auc = 0.8045859336853027 (59.574729191830926 steps/sec)\n",
      "Epoch   0 Batch 5550/14335 Loss: 0.544261 acc: 0.725000 auc = 0.8023891448974609 (51.14926282840044 steps/sec)\n",
      "Epoch   0 Batch 5600/14335 Loss: 0.545034 acc: 0.723125 auc = 0.7915802597999573 (61.95650182960804 steps/sec)\n",
      "Epoch   0 Batch 5650/14335 Loss: 0.543533 acc: 0.718125 auc = 0.7983039021492004 (54.105348920667495 steps/sec)\n",
      "Epoch   0 Batch 5700/14335 Loss: 0.563606 acc: 0.714375 auc = 0.7828166484832764 (53.50020855150457 steps/sec)\n",
      "Epoch   0 Batch 5750/14335 Loss: 0.544864 acc: 0.712500 auc = 0.79841148853302 (62.0923578344987 steps/sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch   0 Batch 5800/14335 Loss: 0.544704 acc: 0.718750 auc = 0.795249342918396 (63.32986458598195 steps/sec)\n",
      "Epoch   0 Batch 5850/14335 Loss: 0.528702 acc: 0.731875 auc = 0.8064228892326355 (54.42442106552542 steps/sec)\n",
      "Epoch   0 Batch 5900/14335 Loss: 0.561774 acc: 0.701875 auc = 0.7776846885681152 (57.840310533344436 steps/sec)\n",
      "Epoch   0 Batch 5950/14335 Loss: 0.531002 acc: 0.721250 auc = 0.8099240660667419 (61.21441531481252 steps/sec)\n",
      "Epoch   0 Batch 6000/14335 Loss: 0.540050 acc: 0.727500 auc = 0.8055544495582581 (55.07397550659395 steps/sec)\n",
      "Epoch   0 Batch 6050/14335 Loss: 0.544347 acc: 0.726250 auc = 0.8019645810127258 (54.64653394888092 steps/sec)\n",
      "Epoch   0 Batch 6100/14335 Loss: 0.552901 acc: 0.704375 auc = 0.7950989603996277 (61.813166812419624 steps/sec)\n",
      "Epoch   0 Batch 6150/14335 Loss: 0.555010 acc: 0.708750 auc = 0.7853560447692871 (60.012488102821386 steps/sec)\n",
      "Epoch   0 Batch 6200/14335 Loss: 0.536463 acc: 0.719375 auc = 0.8073484897613525 (56.92472935569514 steps/sec)\n",
      "Epoch   0 Batch 6250/14335 Loss: 0.545836 acc: 0.715000 auc = 0.7952703237533569 (55.756590273001386 steps/sec)\n",
      "Epoch   0 Batch 6300/14335 Loss: 0.547841 acc: 0.713750 auc = 0.7928528785705566 (55.929154072184716 steps/sec)\n",
      "Epoch   0 Batch 6350/14335 Loss: 0.543664 acc: 0.721250 auc = 0.7961498498916626 (65.27081690917619 steps/sec)\n",
      "Epoch   0 Batch 6400/14335 Loss: 0.537190 acc: 0.728750 auc = 0.8156285285949707 (61.99960088986778 steps/sec)\n",
      "Epoch   0 Batch 6450/14335 Loss: 0.551218 acc: 0.704375 auc = 0.7898125648498535 (63.33667359484017 steps/sec)\n",
      "Epoch   0 Batch 6500/14335 Loss: 0.553371 acc: 0.708750 auc = 0.7823385000228882 (63.557918676006004 steps/sec)\n",
      "Epoch   0 Batch 6550/14335 Loss: 0.525304 acc: 0.748125 auc = 0.8146983981132507 (66.6659461205266 steps/sec)\n",
      "Epoch   0 Batch 6600/14335 Loss: 0.546395 acc: 0.716875 auc = 0.7951645851135254 (59.087953242473525 steps/sec)\n",
      "Epoch   0 Batch 6650/14335 Loss: 0.559491 acc: 0.714375 auc = 0.7887703776359558 (65.43388224751747 steps/sec)\n",
      "Epoch   0 Batch 6700/14335 Loss: 0.525941 acc: 0.727500 auc = 0.815032958984375 (63.05375115567615 steps/sec)\n",
      "Epoch   0 Batch 6750/14335 Loss: 0.553429 acc: 0.699375 auc = 0.7874982953071594 (63.208409575274494 steps/sec)\n",
      "Epoch   0 Batch 6800/14335 Loss: 0.528028 acc: 0.741875 auc = 0.8162024617195129 (61.289839892263956 steps/sec)\n",
      "Epoch   0 Batch 6850/14335 Loss: 0.523681 acc: 0.740625 auc = 0.8150656223297119 (57.69009323550844 steps/sec)\n",
      "Epoch   0 Batch 6900/14335 Loss: 0.546506 acc: 0.721875 auc = 0.7991971373558044 (56.66665856043614 steps/sec)\n",
      "Epoch   0 Batch 6950/14335 Loss: 0.554643 acc: 0.710625 auc = 0.7890881299972534 (61.93099668307803 steps/sec)\n",
      "Epoch   0 Batch 7000/14335 Loss: 0.536404 acc: 0.736250 auc = 0.8029578924179077 (53.79547401741236 steps/sec)\n",
      "Epoch   0 Batch 7050/14335 Loss: 0.549720 acc: 0.717500 auc = 0.7928500175476074 (62.60706539829627 steps/sec)\n",
      "Epoch   0 Batch 7100/14335 Loss: 0.533503 acc: 0.738125 auc = 0.8085582852363586 (60.99985980066097 steps/sec)\n",
      "Epoch   0 Batch 7150/14335 Loss: 0.556065 acc: 0.704375 auc = 0.7780773043632507 (60.65054198335745 steps/sec)\n",
      "Epoch   0 Batch 7200/14335 Loss: 0.532377 acc: 0.719375 auc = 0.8051773309707642 (62.00466021277558 steps/sec)\n",
      "Epoch   0 Batch 7250/14335 Loss: 0.530615 acc: 0.733750 auc = 0.8100563287734985 (61.63174454273853 steps/sec)\n",
      "Epoch   0 Batch 7300/14335 Loss: 0.525469 acc: 0.746875 auc = 0.8170194029808044 (62.3647523433411 steps/sec)\n",
      "Epoch   0 Batch 7350/14335 Loss: 0.542729 acc: 0.728125 auc = 0.8017418384552002 (61.432069023901406 steps/sec)\n",
      "Epoch   0 Batch 7400/14335 Loss: 0.551033 acc: 0.723750 auc = 0.7950109839439392 (56.63424678805555 steps/sec)\n",
      "Epoch   0 Batch 7450/14335 Loss: 0.557407 acc: 0.715625 auc = 0.7888796925544739 (58.38700400048666 steps/sec)\n",
      "Epoch   0 Batch 7500/14335 Loss: 0.537542 acc: 0.715625 auc = 0.7978379130363464 (61.0462753700644 steps/sec)\n",
      "Epoch   0 Batch 7550/14335 Loss: 0.535205 acc: 0.736250 auc = 0.8091744780540466 (65.02863440153031 steps/sec)\n",
      "Epoch   0 Batch 7600/14335 Loss: 0.549121 acc: 0.711250 auc = 0.7901530265808105 (64.36760723934236 steps/sec)\n",
      "Epoch   0 Batch 7650/14335 Loss: 0.554173 acc: 0.726875 auc = 0.7933938503265381 (60.025800350397034 steps/sec)\n",
      "Epoch   0 Batch 7700/14335 Loss: 0.534151 acc: 0.725625 auc = 0.800823986530304 (49.09637150968711 steps/sec)\n",
      "Epoch   0 Batch 7750/14335 Loss: 0.543842 acc: 0.723750 auc = 0.8038204312324524 (66.85760776142395 steps/sec)\n",
      "Epoch   0 Batch 7800/14335 Loss: 0.552618 acc: 0.721875 auc = 0.7930815815925598 (62.38250584589098 steps/sec)\n",
      "Epoch   0 Batch 7850/14335 Loss: 0.532321 acc: 0.724375 auc = 0.810727059841156 (64.83982292621906 steps/sec)\n",
      "Epoch   0 Batch 7900/14335 Loss: 0.555598 acc: 0.723125 auc = 0.7927186489105225 (65.18617432136848 steps/sec)\n",
      "Epoch   0 Batch 7950/14335 Loss: 0.548285 acc: 0.723125 auc = 0.7979340553283691 (66.55920213456426 steps/sec)\n",
      "Epoch   0 Batch 8000/14335 Loss: 0.532995 acc: 0.749375 auc = 0.8073558211326599 (66.2967343084601 steps/sec)\n",
      "Epoch   0 Batch 8050/14335 Loss: 0.546258 acc: 0.717500 auc = 0.7935596704483032 (66.56106114191714 steps/sec)\n",
      "Epoch   0 Batch 8100/14335 Loss: 0.534459 acc: 0.722500 auc = 0.8055294752120972 (64.9661856460848 steps/sec)\n",
      "Epoch   0 Batch 8150/14335 Loss: 0.539380 acc: 0.711250 auc = 0.7999398112297058 (63.71903189336328 steps/sec)\n",
      "Epoch   0 Batch 8200/14335 Loss: 0.541648 acc: 0.725000 auc = 0.8057194352149963 (60.01286591745209 steps/sec)\n",
      "Epoch   0 Batch 8250/14335 Loss: 0.548432 acc: 0.723125 auc = 0.7963907718658447 (65.84820279148514 steps/sec)\n",
      "Epoch   0 Batch 8300/14335 Loss: 0.561693 acc: 0.705625 auc = 0.7824192643165588 (66.55723761464978 steps/sec)\n",
      "Epoch   0 Batch 8350/14335 Loss: 0.540672 acc: 0.726875 auc = 0.7992772459983826 (61.23879706168522 steps/sec)\n",
      "Epoch   0 Batch 8400/14335 Loss: 0.544717 acc: 0.725000 auc = 0.7951003313064575 (65.5289965884896 steps/sec)\n",
      "Epoch   0 Batch 8450/14335 Loss: 0.555769 acc: 0.728125 auc = 0.7897842526435852 (60.21562925940144 steps/sec)\n",
      "Epoch   0 Batch 8500/14335 Loss: 0.542815 acc: 0.725625 auc = 0.7969197034835815 (59.69844365453247 steps/sec)\n",
      "Epoch   0 Batch 8550/14335 Loss: 0.558248 acc: 0.705000 auc = 0.787395179271698 (67.01405787204726 steps/sec)\n",
      "Epoch   0 Batch 8600/14335 Loss: 0.549478 acc: 0.716875 auc = 0.7977180480957031 (67.70800946745715 steps/sec)\n",
      "Epoch   0 Batch 8650/14335 Loss: 0.540977 acc: 0.721250 auc = 0.8043578267097473 (66.88204291493999 steps/sec)\n",
      "Epoch   0 Batch 8700/14335 Loss: 0.557172 acc: 0.716250 auc = 0.7850150465965271 (65.23532630385763 steps/sec)\n",
      "Epoch   0 Batch 8750/14335 Loss: 0.548594 acc: 0.717500 auc = 0.7925693988800049 (66.91962600479859 steps/sec)\n",
      "Epoch   0 Batch 8800/14335 Loss: 0.536609 acc: 0.730000 auc = 0.8030036687850952 (59.39794617525627 steps/sec)\n",
      "Epoch   0 Batch 8850/14335 Loss: 0.523723 acc: 0.744375 auc = 0.8160335421562195 (57.65919534272842 steps/sec)\n",
      "Epoch   0 Batch 8900/14335 Loss: 0.555822 acc: 0.705625 auc = 0.7840352058410645 (62.94011368615658 steps/sec)\n",
      "Epoch   0 Batch 8950/14335 Loss: 0.561473 acc: 0.700625 auc = 0.7789357900619507 (67.75427496226455 steps/sec)\n",
      "Epoch   0 Batch 9000/14335 Loss: 0.558385 acc: 0.722500 auc = 0.7923471331596375 (67.95767162848092 steps/sec)\n",
      "Epoch   0 Batch 9050/14335 Loss: 0.529526 acc: 0.746250 auc = 0.8182609677314758 (67.34451593014276 steps/sec)\n",
      "Epoch   0 Batch 9100/14335 Loss: 0.538147 acc: 0.725625 auc = 0.8074718713760376 (65.90461273711527 steps/sec)\n",
      "Epoch   0 Batch 9150/14335 Loss: 0.557167 acc: 0.720000 auc = 0.7840017080307007 (67.3091761080977 steps/sec)\n",
      "Epoch   0 Batch 9200/14335 Loss: 0.559961 acc: 0.704375 auc = 0.7813671231269836 (66.81062138613231 steps/sec)\n",
      "Epoch   0 Batch 9250/14335 Loss: 0.551602 acc: 0.708750 auc = 0.7905317544937134 (65.0686848390714 steps/sec)\n",
      "Epoch   0 Batch 9300/14335 Loss: 0.549298 acc: 0.711875 auc = 0.7865883111953735 (64.71832441990723 steps/sec)\n",
      "Epoch   0 Batch 9350/14335 Loss: 0.533549 acc: 0.732500 auc = 0.8072716593742371 (66.95564805145091 steps/sec)\n",
      "Epoch   0 Batch 9400/14335 Loss: 0.535756 acc: 0.726250 auc = 0.803879976272583 (67.0009549420086 steps/sec)\n",
      "Epoch   0 Batch 9450/14335 Loss: 0.549938 acc: 0.716875 auc = 0.789318323135376 (66.62945176863433 steps/sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch   0 Batch 9500/14335 Loss: 0.532245 acc: 0.735000 auc = 0.8071315884590149 (67.5489372201166 steps/sec)\n",
      "Epoch   0 Batch 9550/14335 Loss: 0.538259 acc: 0.734375 auc = 0.8036138415336609 (61.3281778897091 steps/sec)\n",
      "Epoch   0 Batch 9600/14335 Loss: 0.545958 acc: 0.728750 auc = 0.7959823608398438 (59.90669858031129 steps/sec)\n",
      "Epoch   0 Batch 9650/14335 Loss: 0.544338 acc: 0.717500 auc = 0.7992711067199707 (65.027948828543 steps/sec)\n",
      "Epoch   0 Batch 9700/14335 Loss: 0.554920 acc: 0.710625 auc = 0.7832721471786499 (67.62742023799773 steps/sec)\n",
      "Epoch   0 Batch 9750/14335 Loss: 0.525200 acc: 0.725625 auc = 0.8095100522041321 (67.85915828384752 steps/sec)\n",
      "Epoch   0 Batch 9800/14335 Loss: 0.537463 acc: 0.723750 auc = 0.8084307312965393 (66.24789574720599 steps/sec)\n",
      "Epoch   0 Batch 9850/14335 Loss: 0.562906 acc: 0.707500 auc = 0.7870272994041443 (57.125688380027995 steps/sec)\n",
      "Epoch   0 Batch 9900/14335 Loss: 0.532981 acc: 0.731250 auc = 0.7973166108131409 (61.99397427953856 steps/sec)\n",
      "Epoch   0 Batch 9950/14335 Loss: 0.544719 acc: 0.718125 auc = 0.7996199727058411 (67.21042163550811 steps/sec)\n",
      "Epoch   0 Batch 10000/14335 Loss: 0.550648 acc: 0.706875 auc = 0.7853096723556519 (65.73561028911855 steps/sec)\n",
      "Epoch   0 Batch 10050/14335 Loss: 0.555703 acc: 0.721875 auc = 0.7927665710449219 (66.702777490637 steps/sec)\n",
      "Epoch   0 Batch 10100/14335 Loss: 0.570810 acc: 0.700000 auc = 0.7717883586883545 (68.14291363438599 steps/sec)\n",
      "Epoch   0 Batch 10150/14335 Loss: 0.559245 acc: 0.714375 auc = 0.7824767231941223 (67.81674056333938 steps/sec)\n",
      "Epoch   0 Batch 10200/14335 Loss: 0.556623 acc: 0.709375 auc = 0.7892614603042603 (67.67530085412496 steps/sec)\n",
      "Epoch   0 Batch 10250/14335 Loss: 0.533903 acc: 0.735000 auc = 0.8034990429878235 (67.55331074203399 steps/sec)\n",
      "Epoch   0 Batch 10300/14335 Loss: 0.535550 acc: 0.729375 auc = 0.8067376613616943 (67.40514466146234 steps/sec)\n",
      "Epoch   0 Batch 10350/14335 Loss: 0.546892 acc: 0.715000 auc = 0.7908911108970642 (67.73534550112609 steps/sec)\n",
      "Epoch   0 Batch 10400/14335 Loss: 0.539095 acc: 0.730000 auc = 0.8015595078468323 (67.92157553679094 steps/sec)\n",
      "Epoch   0 Batch 10450/14335 Loss: 0.533017 acc: 0.742500 auc = 0.8103933930397034 (67.84001656250405 steps/sec)\n",
      "Epoch   0 Batch 10500/14335 Loss: 0.534384 acc: 0.711875 auc = 0.8000807166099548 (67.19056773036012 steps/sec)\n",
      "Epoch   0 Batch 10550/14335 Loss: 0.549915 acc: 0.718750 auc = 0.7851573824882507 (67.25229970481043 steps/sec)\n",
      "Epoch   0 Batch 10600/14335 Loss: 0.558117 acc: 0.710625 auc = 0.7903682589530945 (66.56644862471052 steps/sec)\n",
      "Epoch   0 Batch 10650/14335 Loss: 0.539482 acc: 0.724375 auc = 0.8074131011962891 (67.60128255836031 steps/sec)\n",
      "Epoch   0 Batch 10700/14335 Loss: 0.556783 acc: 0.716250 auc = 0.784888744354248 (66.056567033579 steps/sec)\n",
      "Epoch   0 Batch 10750/14335 Loss: 0.536427 acc: 0.713125 auc = 0.8053316473960876 (67.16711131893578 steps/sec)\n",
      "Epoch   0 Batch 10800/14335 Loss: 0.549944 acc: 0.721250 auc = 0.7961515188217163 (63.08981087665317 steps/sec)\n",
      "Epoch   0 Batch 10850/14335 Loss: 0.538049 acc: 0.735000 auc = 0.8091456890106201 (63.11713444299479 steps/sec)\n",
      "Epoch   0 Batch 10900/14335 Loss: 0.552555 acc: 0.718125 auc = 0.7917004227638245 (64.71381103085301 steps/sec)\n",
      "Epoch   0 Batch 10950/14335 Loss: 0.536575 acc: 0.733125 auc = 0.8036597967147827 (68.16111899639783 steps/sec)\n",
      "Epoch   0 Batch 11000/14335 Loss: 0.551736 acc: 0.712500 auc = 0.783572256565094 (67.50710189550195 steps/sec)\n",
      "Epoch   0 Batch 11050/14335 Loss: 0.538133 acc: 0.715625 auc = 0.8039132952690125 (68.34647096072139 steps/sec)\n",
      "Epoch   0 Batch 11100/14335 Loss: 0.554411 acc: 0.722500 auc = 0.7895137667655945 (67.83034005539238 steps/sec)\n",
      "Epoch   0 Batch 11150/14335 Loss: 0.550677 acc: 0.723125 auc = 0.7920505404472351 (68.23721271352274 steps/sec)\n",
      "Epoch   0 Batch 11200/14335 Loss: 0.533029 acc: 0.736875 auc = 0.8077892065048218 (67.49204604188002 steps/sec)\n",
      "Epoch   0 Batch 11250/14335 Loss: 0.542908 acc: 0.732500 auc = 0.8026555776596069 (67.0416507226515 steps/sec)\n",
      "Epoch   0 Batch 11300/14335 Loss: 0.570376 acc: 0.703750 auc = 0.7734487056732178 (67.86280345936066 steps/sec)\n",
      "Epoch   0 Batch 11350/14335 Loss: 0.536457 acc: 0.720625 auc = 0.8033897876739502 (68.46586846756611 steps/sec)\n",
      "Epoch   0 Batch 11400/14335 Loss: 0.548904 acc: 0.701875 auc = 0.7892175316810608 (68.57893297998831 steps/sec)\n",
      "Epoch   0 Batch 11450/14335 Loss: 0.536825 acc: 0.720000 auc = 0.8058393597602844 (67.76158697314095 steps/sec)\n",
      "Epoch   0 Batch 11500/14335 Loss: 0.534208 acc: 0.742500 auc = 0.8110161423683167 (68.08935064935065 steps/sec)\n",
      "Epoch   0 Batch 11550/14335 Loss: 0.521572 acc: 0.715000 auc = 0.8105992674827576 (68.21672545067103 steps/sec)\n",
      "Epoch   0 Batch 11600/14335 Loss: 0.536660 acc: 0.723125 auc = 0.8004367351531982 (68.20345857858943 steps/sec)\n",
      "Epoch   0 Batch 11650/14335 Loss: 0.538268 acc: 0.730625 auc = 0.8059223890304565 (68.30964926824072 steps/sec)\n",
      "Epoch   0 Batch 11700/14335 Loss: 0.557264 acc: 0.711875 auc = 0.7845372557640076 (67.70372517831068 steps/sec)\n",
      "Epoch   0 Batch 11750/14335 Loss: 0.547358 acc: 0.728125 auc = 0.8028485178947449 (68.57855174035302 steps/sec)\n",
      "Epoch   0 Batch 11800/14335 Loss: 0.540414 acc: 0.725625 auc = 0.8037171959877014 (68.37193986835199 steps/sec)\n",
      "Epoch   0 Batch 11850/14335 Loss: 0.541545 acc: 0.724375 auc = 0.803998589515686 (67.98891248318232 steps/sec)\n",
      "Epoch   0 Batch 11900/14335 Loss: 0.543550 acc: 0.737500 auc = 0.8022405505180359 (67.0164777644131 steps/sec)\n",
      "Epoch   0 Batch 11950/14335 Loss: 0.531593 acc: 0.732500 auc = 0.8082790970802307 (66.61453088917759 steps/sec)\n",
      "Epoch   0 Batch 12000/14335 Loss: 0.549587 acc: 0.713750 auc = 0.7958033084869385 (66.88720515309905 steps/sec)\n",
      "Epoch   0 Batch 12050/14335 Loss: 0.538550 acc: 0.731875 auc = 0.7987227439880371 (68.41085947757725 steps/sec)\n",
      "Epoch   0 Batch 12100/14335 Loss: 0.543821 acc: 0.726875 auc = 0.7975229620933533 (68.44861699426275 steps/sec)\n",
      "Epoch   0 Batch 12150/14335 Loss: 0.539779 acc: 0.735000 auc = 0.8057572245597839 (68.14605790467847 steps/sec)\n",
      "Epoch   0 Batch 12200/14335 Loss: 0.553931 acc: 0.713750 auc = 0.7919602990150452 (66.8899999202609 steps/sec)\n",
      "Epoch   0 Batch 12250/14335 Loss: 0.548159 acc: 0.711875 auc = 0.7969074845314026 (66.29243815208918 steps/sec)\n",
      "Epoch   0 Batch 12300/14335 Loss: 0.552188 acc: 0.709375 auc = 0.7933695316314697 (67.29420840054512 steps/sec)\n",
      "Epoch   0 Batch 12350/14335 Loss: 0.542935 acc: 0.735625 auc = 0.8008410930633545 (64.86210301903938 steps/sec)\n",
      "Epoch   0 Batch 12400/14335 Loss: 0.547989 acc: 0.707500 auc = 0.785950779914856 (64.84274994960133 steps/sec)\n",
      "Epoch   0 Batch 12450/14335 Loss: 0.537273 acc: 0.731250 auc = 0.8021483421325684 (67.94364682231773 steps/sec)\n",
      "Epoch   0 Batch 12500/14335 Loss: 0.526289 acc: 0.747500 auc = 0.8157688975334167 (68.24391869376875 steps/sec)\n",
      "Epoch   0 Batch 12550/14335 Loss: 0.537490 acc: 0.725625 auc = 0.8036500811576843 (65.0592781394333 steps/sec)\n",
      "Epoch   0 Batch 12600/14335 Loss: 0.561320 acc: 0.710000 auc = 0.7789747714996338 (62.31657019243341 steps/sec)\n",
      "Epoch   0 Batch 12650/14335 Loss: 0.523313 acc: 0.744375 auc = 0.8120877742767334 (67.49962744322411 steps/sec)\n",
      "Epoch   0 Batch 12700/14335 Loss: 0.546648 acc: 0.718125 auc = 0.8028371334075928 (66.18569533180079 steps/sec)\n",
      "Epoch   0 Batch 12750/14335 Loss: 0.549111 acc: 0.725625 auc = 0.7948368191719055 (66.97662535090717 steps/sec)\n",
      "Epoch   0 Batch 12800/14335 Loss: 0.544296 acc: 0.708125 auc = 0.7967571020126343 (67.59927783287975 steps/sec)\n",
      "Epoch   0 Batch 12850/14335 Loss: 0.560364 acc: 0.708125 auc = 0.7762905359268188 (67.84453760036025 steps/sec)\n",
      "Epoch   0 Batch 12900/14335 Loss: 0.526486 acc: 0.738125 auc = 0.815148115158081 (67.00337388815049 steps/sec)\n",
      "Epoch   0 Batch 12950/14335 Loss: 0.544413 acc: 0.726875 auc = 0.793749213218689 (68.30722408096474 steps/sec)\n",
      "Epoch   0 Batch 13000/14335 Loss: 0.544740 acc: 0.729375 auc = 0.7997493147850037 (68.72350347148148 steps/sec)\n",
      "Epoch   0 Batch 13050/14335 Loss: 0.547415 acc: 0.711875 auc = 0.7930786609649658 (67.21804761910867 steps/sec)\n",
      "Epoch   0 Batch 13100/14335 Loss: 0.541309 acc: 0.731875 auc = 0.8045042157173157 (68.19179332068012 steps/sec)\n",
      "Epoch   0 Batch 13150/14335 Loss: 0.540922 acc: 0.722500 auc = 0.8006638884544373 (60.02920236217971 steps/sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch   0 Batch 13200/14335 Loss: 0.540726 acc: 0.720000 auc = 0.7981392741203308 (68.00315444319926 steps/sec)\n",
      "Epoch   0 Batch 13250/14335 Loss: 0.548992 acc: 0.727500 auc = 0.7858895063400269 (68.01700528917944 steps/sec)\n",
      "Epoch   0 Batch 13300/14335 Loss: 0.562392 acc: 0.711250 auc = 0.7852771878242493 (67.69336643407702 steps/sec)\n",
      "Epoch   0 Batch 13350/14335 Loss: 0.532343 acc: 0.723750 auc = 0.8040519952774048 (68.0880463653456 steps/sec)\n",
      "Epoch   0 Batch 13400/14335 Loss: 0.547885 acc: 0.719375 auc = 0.794984757900238 (66.83615111587886 steps/sec)\n",
      "Epoch   0 Batch 13450/14335 Loss: 0.565702 acc: 0.725000 auc = 0.780591607093811 (68.49153829924681 steps/sec)\n",
      "Epoch   0 Batch 13500/14335 Loss: 0.562364 acc: 0.703125 auc = 0.7783322334289551 (67.47773508752003 steps/sec)\n",
      "Epoch   0 Batch 13550/14335 Loss: 0.548451 acc: 0.709375 auc = 0.7890747785568237 (68.04145653319353 steps/sec)\n",
      "Epoch   0 Batch 13600/14335 Loss: 0.578140 acc: 0.687500 auc = 0.7622549533843994 (67.11032432065721 steps/sec)\n",
      "Epoch   0 Batch 13650/14335 Loss: 0.538132 acc: 0.720000 auc = 0.8020890951156616 (68.24112067422676 steps/sec)\n",
      "Epoch   0 Batch 13700/14335 Loss: 0.528728 acc: 0.743125 auc = 0.81407630443573 (64.69785944892031 steps/sec)\n",
      "Epoch   0 Batch 13750/14335 Loss: 0.564053 acc: 0.707500 auc = 0.7845285534858704 (67.29846261274965 steps/sec)\n",
      "Epoch   0 Batch 13800/14335 Loss: 0.527934 acc: 0.743125 auc = 0.8169074058532715 (68.47288774655962 steps/sec)\n",
      "Epoch   0 Batch 13850/14335 Loss: 0.558038 acc: 0.716875 auc = 0.7834619879722595 (67.67613074196964 steps/sec)\n",
      "Epoch   0 Batch 13900/14335 Loss: 0.556140 acc: 0.713750 auc = 0.7872093915939331 (67.6653219548537 steps/sec)\n",
      "Epoch   0 Batch 13950/14335 Loss: 0.514208 acc: 0.738750 auc = 0.8229831457138062 (67.72637684978591 steps/sec)\n",
      "Epoch   0 Batch 14000/14335 Loss: 0.535155 acc: 0.720625 auc = 0.8004268407821655 (65.87296077968836 steps/sec)\n",
      "Epoch   0 Batch 14050/14335 Loss: 0.564309 acc: 0.698125 auc = 0.7766571640968323 (66.19589028124112 steps/sec)\n",
      "Epoch   0 Batch 14100/14335 Loss: 0.535823 acc: 0.735625 auc = 0.8042635917663574 (66.95573355912094 steps/sec)\n",
      "Epoch   0 Batch 14150/14335 Loss: 0.535203 acc: 0.735625 auc = 0.8133327960968018 (68.25806774992864 steps/sec)\n",
      "Epoch   0 Batch 14200/14335 Loss: 0.537376 acc: 0.715625 auc = 0.8046760559082031 (67.24774943194681 steps/sec)\n",
      "Epoch   0 Batch 14250/14335 Loss: 0.538793 acc: 0.735625 auc = 0.8005168437957764 (64.73246778581618 steps/sec)\n",
      "Epoch   0 Batch 14300/14335 Loss: 0.549058 acc: 0.721875 auc = 0.7925262451171875 (64.43275023411634 steps/sec)\n",
      "\n",
      "Train time for epoch #1 : 228.89420914649963\n",
      "Model test set loss: 0.560902  acc: 0.706340  auc = 0.7790570259094238 prediction = 0.43587207794189453\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "         0.0       0.87      0.71      0.78     74423\n",
      "         1.0       0.45      0.70      0.55     25577\n",
      "\n",
      "   micro avg       0.71      0.71      0.71    100000\n",
      "   macro avg       0.66      0.71      0.67    100000\n",
      "weighted avg       0.77      0.71      0.72    100000\n",
      "\n",
      "best loss = 0.5609018206596375\n"
     ]
    }
   ],
   "source": [
    "ctr_net=ctr_network()\n",
    "ctr_net.training((train_X, train_y), (test_X, test_y), True, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从训练一轮的结果看，下采样的训练使得网络能够对用户点击预测的更好，跟全数据训练比起来，下采样的数据更均衡。预测成1的recall和f1 score比全数据训练略高一些，说明false negative变少了，提高了用户点击预测的能力。因为网络更主动预测出用户点击事件，造成了false positive增加，导致1的precision降低了一些。采用下采样训练避免了数据不均衡，增加训练次数有助于提高网络的预测能力。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 全数据的训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_8\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "sparse_input (InputLayer)       [(None, 26)]         0                                            \n",
      "__________________________________________________________________________________________________\n",
      "embedding_8 (Embedding)         (None, 26, 32)       960000      sparse_input[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "dense_input (InputLayer)        [(None, 13)]         0                                            \n",
      "__________________________________________________________________________________________________\n",
      "reshape_8 (Reshape)             (None, 832)          0           embedding_8[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_16 (Concatenate)    (None, 845)          0           dense_input[0][0]                \n",
      "                                                                 reshape_8[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "fc1_layer (Dense)               (None, 400)          338400      concatenate_16[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "FFM_input (InputLayer)          [(None, 1)]          0                                            \n",
      "__________________________________________________________________________________________________\n",
      "FM_input (InputLayer)           [(None, 1)]          0                                            \n",
      "__________________________________________________________________________________________________\n",
      "fc2_layer (Dense)               (None, 400)          160400      fc1_layer[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "ffm_fc_layer (Dense)            (None, 1)            2           FFM_input[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "fm_fc_layer (Dense)             (None, 1)            2           FM_input[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "fc3_layer (Dense)               (None, 400)          160400      fc2_layer[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_17 (Concatenate)    (None, 402)          0           ffm_fc_layer[0][0]               \n",
      "                                                                 fm_fc_layer[0][0]                \n",
      "                                                                 fc3_layer[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "logits_layer (Dense)            (None, 1)            403         concatenate_17[0][0]             \n",
      "==================================================================================================\n",
      "Total params: 1,619,607\n",
      "Trainable params: 1,619,607\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "Epoch   0 Batch    0/28124 Loss: 0.695642 acc: 0.593750 auc = 0.4444444477558136 (24.438443068206514 steps/sec)\n",
      "Epoch   0 Batch   50/28124 Loss: 0.676262 acc: 0.754375 auc = 0.7052719593048096 (56.8895679093392 steps/sec)\n",
      "Epoch   0 Batch  100/28124 Loss: 0.659834 acc: 0.758125 auc = 0.7097333669662476 (57.351932937286364 steps/sec)\n",
      "Epoch   0 Batch  150/28124 Loss: 0.651092 acc: 0.751250 auc = 0.7365592122077942 (54.82353304087521 steps/sec)\n",
      "Epoch   0 Batch  200/28124 Loss: 0.646103 acc: 0.739375 auc = 0.7396945953369141 (55.27255936098272 steps/sec)\n",
      "Epoch   0 Batch  250/28124 Loss: 0.633896 acc: 0.759375 auc = 0.7329022884368896 (58.166326440046156 steps/sec)\n",
      "Epoch   0 Batch  300/28124 Loss: 0.631026 acc: 0.738750 auc = 0.7378382682800293 (48.374017308200656 steps/sec)\n",
      "Epoch   0 Batch  350/28124 Loss: 0.620605 acc: 0.739375 auc = 0.7579983472824097 (56.053874105762276 steps/sec)\n",
      "Epoch   0 Batch  400/28124 Loss: 0.608071 acc: 0.741250 auc = 0.7419705390930176 (57.51437960962716 steps/sec)\n",
      "Epoch   0 Batch  450/28124 Loss: 0.595344 acc: 0.736875 auc = 0.7699739933013916 (58.214603950089526 steps/sec)\n",
      "Epoch   0 Batch  500/28124 Loss: 0.574273 acc: 0.748750 auc = 0.7903768420219421 (54.461719847611725 steps/sec)\n",
      "Epoch   0 Batch  550/28124 Loss: 0.556080 acc: 0.753750 auc = 0.7929779887199402 (48.8447891721024 steps/sec)\n",
      "Epoch   0 Batch  600/28124 Loss: 0.542671 acc: 0.756250 auc = 0.7925984263420105 (51.27958601765484 steps/sec)\n",
      "Epoch   0 Batch  650/28124 Loss: 0.538169 acc: 0.744375 auc = 0.8030697703361511 (56.83457351278062 steps/sec)\n",
      "Epoch   0 Batch  700/28124 Loss: 0.522292 acc: 0.756250 auc = 0.7760412096977234 (50.95718206067863 steps/sec)\n",
      "Epoch   0 Batch  750/28124 Loss: 0.506857 acc: 0.763750 auc = 0.8062525391578674 (45.946707435115115 steps/sec)\n",
      "Epoch   0 Batch  800/28124 Loss: 0.523459 acc: 0.736250 auc = 0.8096563220024109 (50.86413033855787 steps/sec)\n",
      "Epoch   0 Batch  850/28124 Loss: 0.518308 acc: 0.748125 auc = 0.7848278284072876 (59.70078892133874 steps/sec)\n",
      "Epoch   0 Batch  900/28124 Loss: 0.515997 acc: 0.747500 auc = 0.7800781726837158 (60.661927839232376 steps/sec)\n",
      "Epoch   0 Batch  950/28124 Loss: 0.499978 acc: 0.756250 auc = 0.8099327087402344 (58.023016618502105 steps/sec)\n",
      "Epoch   0 Batch 1000/28124 Loss: 0.513409 acc: 0.735000 auc = 0.8067871928215027 (59.929021976097 steps/sec)\n",
      "Epoch   0 Batch 1050/28124 Loss: 0.487284 acc: 0.766875 auc = 0.7960397601127625 (55.624467368681266 steps/sec)\n",
      "Epoch   0 Batch 1100/28124 Loss: 0.494707 acc: 0.756250 auc = 0.7939921021461487 (51.22925420546547 steps/sec)\n",
      "Epoch   0 Batch 1150/28124 Loss: 0.500633 acc: 0.752500 auc = 0.7836312651634216 (54.40087242610046 steps/sec)\n",
      "Epoch   0 Batch 1200/28124 Loss: 0.500350 acc: 0.756250 auc = 0.7797181606292725 (56.09971275390837 steps/sec)\n",
      "Epoch   0 Batch 1250/28124 Loss: 0.461751 acc: 0.781250 auc = 0.7985043525695801 (59.97260391495203 steps/sec)\n",
      "Epoch   0 Batch 1300/28124 Loss: 0.502038 acc: 0.739375 auc = 0.8029755353927612 (59.461589803175706 steps/sec)\n",
      "Epoch   0 Batch 1350/28124 Loss: 0.516052 acc: 0.738125 auc = 0.7925316691398621 (61.569156939474304 steps/sec)\n",
      "Epoch   0 Batch 1400/28124 Loss: 0.480229 acc: 0.765625 auc = 0.788816511631012 (58.548542492635896 steps/sec)\n",
      "Epoch   0 Batch 1450/28124 Loss: 0.494893 acc: 0.753125 auc = 0.7910218238830566 (57.64253881450233 steps/sec)\n",
      "Epoch   0 Batch 1500/28124 Loss: 0.493439 acc: 0.759375 auc = 0.7848734259605408 (56.71398078138467 steps/sec)\n",
      "Epoch   0 Batch 1550/28124 Loss: 0.473574 acc: 0.763750 auc = 0.8046062588691711 (57.88932650084523 steps/sec)\n",
      "Epoch   0 Batch 1600/28124 Loss: 0.476035 acc: 0.769375 auc = 0.7915105223655701 (56.938608230222734 steps/sec)\n",
      "Epoch   0 Batch 1650/28124 Loss: 0.479259 acc: 0.763750 auc = 0.8080615997314453 (60.367521461012664 steps/sec)\n",
      "Epoch   0 Batch 1700/28124 Loss: 0.495410 acc: 0.756875 auc = 0.7829841375350952 (60.64405273018707 steps/sec)\n",
      "Epoch   0 Batch 1750/28124 Loss: 0.468049 acc: 0.765000 auc = 0.810431718826294 (60.497538156554086 steps/sec)\n",
      "Epoch   0 Batch 1800/28124 Loss: 0.461530 acc: 0.783750 auc = 0.8064031004905701 (57.747710635823125 steps/sec)\n",
      "Epoch   0 Batch 1850/28124 Loss: 0.481451 acc: 0.771250 auc = 0.7663798332214355 (59.97994521256302 steps/sec)\n",
      "Epoch   0 Batch 1900/28124 Loss: 0.501134 acc: 0.745625 auc = 0.7970093488693237 (60.752095244965 steps/sec)\n",
      "Epoch   0 Batch 1950/28124 Loss: 0.481226 acc: 0.759375 auc = 0.7998560070991516 (59.90483334409276 steps/sec)\n",
      "Epoch   0 Batch 2000/28124 Loss: 0.481734 acc: 0.762500 auc = 0.795172929763794 (58.19995076813094 steps/sec)\n",
      "Epoch   0 Batch 2050/28124 Loss: 0.461756 acc: 0.775000 auc = 0.8082979321479797 (58.06136173233465 steps/sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch   0 Batch 2100/28124 Loss: 0.498306 acc: 0.749375 auc = 0.7867807745933533 (57.167624479817775 steps/sec)\n",
      "Epoch   0 Batch 2150/28124 Loss: 0.486206 acc: 0.763125 auc = 0.7814154624938965 (57.92440708432928 steps/sec)\n",
      "Epoch   0 Batch 2200/28124 Loss: 0.468975 acc: 0.770000 auc = 0.8009355068206787 (54.45183542872454 steps/sec)\n",
      "Epoch   0 Batch 2250/28124 Loss: 0.458442 acc: 0.780625 auc = 0.8138964176177979 (50.650315472803456 steps/sec)\n",
      "Epoch   0 Batch 2300/28124 Loss: 0.466317 acc: 0.771875 auc = 0.786180853843689 (56.25018440247429 steps/sec)\n",
      "Epoch   0 Batch 2350/28124 Loss: 0.481661 acc: 0.774375 auc = 0.7758103013038635 (58.21167918668329 steps/sec)\n",
      "Epoch   0 Batch 2400/28124 Loss: 0.464186 acc: 0.778125 auc = 0.8015938401222229 (58.04471305515592 steps/sec)\n",
      "Epoch   0 Batch 2450/28124 Loss: 0.449709 acc: 0.795625 auc = 0.7987489104270935 (57.70539582014281 steps/sec)\n",
      "Epoch   0 Batch 2500/28124 Loss: 0.492259 acc: 0.750625 auc = 0.7953976392745972 (57.73484914181729 steps/sec)\n",
      "Epoch   0 Batch 2550/28124 Loss: 0.473976 acc: 0.763750 auc = 0.8038125038146973 (60.41207439508765 steps/sec)\n",
      "Epoch   0 Batch 2600/28124 Loss: 0.483079 acc: 0.764375 auc = 0.7928747534751892 (58.832034512291976 steps/sec)\n",
      "Epoch   0 Batch 2650/28124 Loss: 0.495904 acc: 0.752500 auc = 0.78272545337677 (62.6188051215305 steps/sec)\n",
      "Epoch   0 Batch 2700/28124 Loss: 0.463502 acc: 0.767500 auc = 0.7940940856933594 (59.92107677542254 steps/sec)\n",
      "Epoch   0 Batch 2750/28124 Loss: 0.489970 acc: 0.756250 auc = 0.7957569360733032 (62.11380129644647 steps/sec)\n",
      "Epoch   0 Batch 2800/28124 Loss: 0.469246 acc: 0.772500 auc = 0.789467453956604 (59.866971927080066 steps/sec)\n",
      "Epoch   0 Batch 2850/28124 Loss: 0.445515 acc: 0.784375 auc = 0.8249233365058899 (55.955881038468014 steps/sec)\n",
      "Epoch   0 Batch 2900/28124 Loss: 0.476573 acc: 0.768750 auc = 0.7926992177963257 (52.24376564303378 steps/sec)\n",
      "Epoch   0 Batch 2950/28124 Loss: 0.462424 acc: 0.783125 auc = 0.7817521095275879 (54.45473392078903 steps/sec)\n",
      "Epoch   0 Batch 3000/28124 Loss: 0.486066 acc: 0.753750 auc = 0.7930450439453125 (55.17765416984698 steps/sec)\n",
      "Epoch   0 Batch 3050/28124 Loss: 0.481140 acc: 0.763750 auc = 0.7846483588218689 (45.95465128382117 steps/sec)\n",
      "Epoch   0 Batch 3100/28124 Loss: 0.469396 acc: 0.771875 auc = 0.8035724759101868 (58.18194731433619 steps/sec)\n",
      "Epoch   0 Batch 3150/28124 Loss: 0.460642 acc: 0.780000 auc = 0.8150060772895813 (57.68722093732051 steps/sec)\n",
      "Epoch   0 Batch 3200/28124 Loss: 0.498663 acc: 0.754375 auc = 0.7769438028335571 (62.26284237627901 steps/sec)\n",
      "Epoch   0 Batch 3250/28124 Loss: 0.460812 acc: 0.770625 auc = 0.8248105049133301 (62.59254638586329 steps/sec)\n",
      "Epoch   0 Batch 3300/28124 Loss: 0.488076 acc: 0.766250 auc = 0.7813960313796997 (61.57423664637634 steps/sec)\n",
      "Epoch   0 Batch 3350/28124 Loss: 0.480145 acc: 0.771875 auc = 0.7847239971160889 (62.516734758365146 steps/sec)\n",
      "Epoch   0 Batch 3400/28124 Loss: 0.463838 acc: 0.772500 auc = 0.8101917505264282 (58.11587415513625 steps/sec)\n",
      "Epoch   0 Batch 3450/28124 Loss: 0.458124 acc: 0.785000 auc = 0.7837583422660828 (61.736922038424844 steps/sec)\n",
      "Epoch   0 Batch 3500/28124 Loss: 0.447791 acc: 0.791875 auc = 0.8121086955070496 (61.4415180375062 steps/sec)\n",
      "Epoch   0 Batch 3550/28124 Loss: 0.460966 acc: 0.791875 auc = 0.7764565944671631 (60.70312101999324 steps/sec)\n",
      "Epoch   0 Batch 3600/28124 Loss: 0.452053 acc: 0.795625 auc = 0.7805606722831726 (62.26269449372846 steps/sec)\n",
      "Epoch   0 Batch 3650/28124 Loss: 0.452157 acc: 0.787500 auc = 0.802215039730072 (62.268832209982484 steps/sec)\n",
      "Epoch   0 Batch 3700/28124 Loss: 0.450177 acc: 0.781250 auc = 0.8040798306465149 (62.06699790342992 steps/sec)\n",
      "Epoch   0 Batch 3750/28124 Loss: 0.478983 acc: 0.761875 auc = 0.7984312176704407 (62.09438017008541 steps/sec)\n",
      "Epoch   0 Batch 3800/28124 Loss: 0.459667 acc: 0.781875 auc = 0.7850093841552734 (58.57256410815002 steps/sec)\n",
      "Epoch   0 Batch 3850/28124 Loss: 0.459353 acc: 0.786250 auc = 0.7734257578849792 (58.18228628992321 steps/sec)\n",
      "Epoch   0 Batch 3900/28124 Loss: 0.464087 acc: 0.776250 auc = 0.7855739593505859 (53.72785903979365 steps/sec)\n",
      "Epoch   0 Batch 3950/28124 Loss: 0.444967 acc: 0.798750 auc = 0.7952197194099426 (57.29804517720397 steps/sec)\n",
      "Epoch   0 Batch 4000/28124 Loss: 0.467601 acc: 0.776875 auc = 0.7930358052253723 (61.25911809621512 steps/sec)\n",
      "Epoch   0 Batch 4050/28124 Loss: 0.483713 acc: 0.760625 auc = 0.7773906588554382 (62.21265812721136 steps/sec)\n",
      "Epoch   0 Batch 4100/28124 Loss: 0.463537 acc: 0.770625 auc = 0.810965895652771 (59.760996138186364 steps/sec)\n",
      "Epoch   0 Batch 4150/28124 Loss: 0.445189 acc: 0.791250 auc = 0.8189920783042908 (56.772384145491365 steps/sec)\n",
      "Epoch   0 Batch 4200/28124 Loss: 0.432708 acc: 0.797500 auc = 0.8226805329322815 (59.599668175828164 steps/sec)\n",
      "Epoch   0 Batch 4250/28124 Loss: 0.481355 acc: 0.768125 auc = 0.7779164910316467 (56.41876313853905 steps/sec)\n",
      "Epoch   0 Batch 4300/28124 Loss: 0.454041 acc: 0.786250 auc = 0.8010469079017639 (60.82140944052709 steps/sec)\n",
      "Epoch   0 Batch 4350/28124 Loss: 0.455959 acc: 0.777500 auc = 0.8078991174697876 (61.262697139411756 steps/sec)\n",
      "Epoch   0 Batch 4400/28124 Loss: 0.463034 acc: 0.775625 auc = 0.7980759143829346 (59.30282800542029 steps/sec)\n",
      "Epoch   0 Batch 4450/28124 Loss: 0.474300 acc: 0.762500 auc = 0.7906619906425476 (60.0240823091769 steps/sec)\n",
      "Epoch   0 Batch 4500/28124 Loss: 0.433100 acc: 0.796250 auc = 0.807033896446228 (62.52487993827271 steps/sec)\n",
      "Epoch   0 Batch 4550/28124 Loss: 0.449235 acc: 0.796250 auc = 0.8140391707420349 (57.95064134855765 steps/sec)\n",
      "Epoch   0 Batch 4600/28124 Loss: 0.475027 acc: 0.775000 auc = 0.780977725982666 (61.080181660322694 steps/sec)\n",
      "Epoch   0 Batch 4650/28124 Loss: 0.447991 acc: 0.791875 auc = 0.7907368540763855 (46.00370415949076 steps/sec)\n",
      "Epoch   0 Batch 4700/28124 Loss: 0.472870 acc: 0.776250 auc = 0.7687328457832336 (57.89826050009759 steps/sec)\n",
      "Epoch   0 Batch 4750/28124 Loss: 0.478731 acc: 0.766875 auc = 0.784024178981781 (55.90464324119999 steps/sec)\n",
      "Epoch   0 Batch 4800/28124 Loss: 0.466161 acc: 0.783750 auc = 0.795582115650177 (56.572937382047094 steps/sec)\n",
      "Epoch   0 Batch 4850/28124 Loss: 0.437712 acc: 0.798750 auc = 0.8237354755401611 (58.85434031227303 steps/sec)\n",
      "Epoch   0 Batch 4900/28124 Loss: 0.447153 acc: 0.792500 auc = 0.7843477725982666 (57.8822803358309 steps/sec)\n",
      "Epoch   0 Batch 4950/28124 Loss: 0.451306 acc: 0.789375 auc = 0.7946956753730774 (61.67972572305193 steps/sec)\n",
      "Epoch   0 Batch 5000/28124 Loss: 0.481761 acc: 0.768750 auc = 0.7754953503608704 (62.404763010018556 steps/sec)\n",
      "Epoch   0 Batch 5050/28124 Loss: 0.461939 acc: 0.776250 auc = 0.7965489029884338 (59.42426958358139 steps/sec)\n",
      "Epoch   0 Batch 5100/28124 Loss: 0.447653 acc: 0.793750 auc = 0.7932068705558777 (61.51236112325104 steps/sec)\n",
      "Epoch   0 Batch 5150/28124 Loss: 0.458532 acc: 0.783750 auc = 0.7902125716209412 (62.080502244297634 steps/sec)\n",
      "Epoch   0 Batch 5200/28124 Loss: 0.445644 acc: 0.791250 auc = 0.791350245475769 (61.529758939359 steps/sec)\n",
      "Epoch   0 Batch 5250/28124 Loss: 0.469660 acc: 0.771875 auc = 0.7882238626480103 (57.325313291429026 steps/sec)\n",
      "Epoch   0 Batch 5300/28124 Loss: 0.442436 acc: 0.793750 auc = 0.8050605654716492 (53.68056364346096 steps/sec)\n",
      "Epoch   0 Batch 5350/28124 Loss: 0.469809 acc: 0.776875 auc = 0.7869734168052673 (49.20770081070675 steps/sec)\n",
      "Epoch   0 Batch 5400/28124 Loss: 0.451795 acc: 0.783125 auc = 0.8086296319961548 (57.06349724634842 steps/sec)\n",
      "Epoch   0 Batch 5450/28124 Loss: 0.487201 acc: 0.758125 auc = 0.783725380897522 (59.510640622361834 steps/sec)\n",
      "Epoch   0 Batch 5500/28124 Loss: 0.444823 acc: 0.797500 auc = 0.7961276173591614 (60.71726883003669 steps/sec)\n",
      "Epoch   0 Batch 5550/28124 Loss: 0.449965 acc: 0.783125 auc = 0.8070613145828247 (46.790936647834144 steps/sec)\n",
      "Epoch   0 Batch 5600/28124 Loss: 0.439901 acc: 0.803750 auc = 0.8013973832130432 (57.244071082320396 steps/sec)\n",
      "Epoch   0 Batch 5650/28124 Loss: 0.455141 acc: 0.782500 auc = 0.7997117042541504 (52.30995178953418 steps/sec)\n",
      "Epoch   0 Batch 5700/28124 Loss: 0.466942 acc: 0.772500 auc = 0.7791428565979004 (48.06065149202954 steps/sec)\n",
      "Epoch   0 Batch 5750/28124 Loss: 0.466285 acc: 0.777500 auc = 0.794087827205658 (51.830494684608226 steps/sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch   0 Batch 5800/28124 Loss: 0.444486 acc: 0.787500 auc = 0.8115587830543518 (45.802105564781805 steps/sec)\n",
      "Epoch   0 Batch 5850/28124 Loss: 0.454069 acc: 0.783750 auc = 0.7921735644340515 (54.120177311379564 steps/sec)\n",
      "Epoch   0 Batch 5900/28124 Loss: 0.481054 acc: 0.773125 auc = 0.7705696225166321 (51.15974417590846 steps/sec)\n",
      "Epoch   0 Batch 5950/28124 Loss: 0.438279 acc: 0.797500 auc = 0.8236971497535706 (54.90040239052064 steps/sec)\n",
      "Epoch   0 Batch 6000/28124 Loss: 0.433470 acc: 0.796250 auc = 0.8210312724113464 (45.462107142756494 steps/sec)\n",
      "Epoch   0 Batch 6050/28124 Loss: 0.461410 acc: 0.783750 auc = 0.7905995845794678 (55.74994995628319 steps/sec)\n",
      "Epoch   0 Batch 6100/28124 Loss: 0.435572 acc: 0.796250 auc = 0.8237715363502502 (60.841013096261086 steps/sec)\n",
      "Epoch   0 Batch 6150/28124 Loss: 0.431955 acc: 0.798125 auc = 0.8219204545021057 (61.48768898690762 steps/sec)\n",
      "Epoch   0 Batch 6200/28124 Loss: 0.459346 acc: 0.785000 auc = 0.7797780632972717 (62.42367272244523 steps/sec)\n",
      "Epoch   0 Batch 6250/28124 Loss: 0.450573 acc: 0.787500 auc = 0.8039199113845825 (58.368592236009114 steps/sec)\n",
      "Epoch   0 Batch 6300/28124 Loss: 0.451488 acc: 0.793125 auc = 0.7906412482261658 (59.71605465231801 steps/sec)\n",
      "Epoch   0 Batch 6350/28124 Loss: 0.478597 acc: 0.767500 auc = 0.7840747833251953 (60.224707743239065 steps/sec)\n",
      "Epoch   0 Batch 6400/28124 Loss: 0.461495 acc: 0.782500 auc = 0.798947274684906 (60.67784713126268 steps/sec)\n",
      "Epoch   0 Batch 6450/28124 Loss: 0.451203 acc: 0.794375 auc = 0.801008939743042 (60.570225754314706 steps/sec)\n",
      "Epoch   0 Batch 6500/28124 Loss: 0.458311 acc: 0.786250 auc = 0.7840520739555359 (62.70078793361912 steps/sec)\n",
      "Epoch   0 Batch 6550/28124 Loss: 0.452714 acc: 0.790625 auc = 0.8082153797149658 (62.3410967194967 steps/sec)\n",
      "Epoch   0 Batch 6600/28124 Loss: 0.457802 acc: 0.782500 auc = 0.7871213555335999 (59.62061069027817 steps/sec)\n",
      "Epoch   0 Batch 6650/28124 Loss: 0.474168 acc: 0.768125 auc = 0.8031589984893799 (60.270366429913544 steps/sec)\n",
      "Epoch   0 Batch 6700/28124 Loss: 0.456512 acc: 0.776875 auc = 0.8062469959259033 (55.05140777798749 steps/sec)\n",
      "Epoch   0 Batch 6750/28124 Loss: 0.431572 acc: 0.804375 auc = 0.8122795224189758 (57.62931237027818 steps/sec)\n",
      "Epoch   0 Batch 6800/28124 Loss: 0.482157 acc: 0.766875 auc = 0.7728848457336426 (53.406948257333056 steps/sec)\n",
      "Epoch   0 Batch 6850/28124 Loss: 0.439603 acc: 0.805000 auc = 0.8032812476158142 (54.222689917560075 steps/sec)\n",
      "Epoch   0 Batch 6900/28124 Loss: 0.430993 acc: 0.808125 auc = 0.8108697533607483 (58.74964492237597 steps/sec)\n",
      "Epoch   0 Batch 6950/28124 Loss: 0.469360 acc: 0.775000 auc = 0.7846802473068237 (58.41899624663565 steps/sec)\n",
      "Epoch   0 Batch 7000/28124 Loss: 0.448956 acc: 0.790625 auc = 0.7948833703994751 (57.86642075910164 steps/sec)\n",
      "Epoch   0 Batch 7050/28124 Loss: 0.445701 acc: 0.785000 auc = 0.8130139112472534 (58.87104358134577 steps/sec)\n",
      "Epoch   0 Batch 7100/28124 Loss: 0.437277 acc: 0.799375 auc = 0.8018577098846436 (59.444398147124566 steps/sec)\n",
      "Epoch   0 Batch 7150/28124 Loss: 0.438401 acc: 0.788750 auc = 0.8102893233299255 (59.84075010950035 steps/sec)\n",
      "Epoch   0 Batch 7200/28124 Loss: 0.437215 acc: 0.799375 auc = 0.8081187605857849 (57.143588951296316 steps/sec)\n",
      "Epoch   0 Batch 7250/28124 Loss: 0.448089 acc: 0.793750 auc = 0.7961254715919495 (57.7439740118635 steps/sec)\n",
      "Epoch   0 Batch 7300/28124 Loss: 0.478560 acc: 0.776875 auc = 0.7819251418113708 (46.99273872519307 steps/sec)\n",
      "Epoch   0 Batch 7350/28124 Loss: 0.448437 acc: 0.787500 auc = 0.8089509010314941 (61.93591677266677 steps/sec)\n",
      "Epoch   0 Batch 7400/28124 Loss: 0.456947 acc: 0.789375 auc = 0.7878843545913696 (61.219811945901604 steps/sec)\n",
      "Epoch   0 Batch 7450/28124 Loss: 0.457881 acc: 0.794375 auc = 0.7894827127456665 (61.775985346867486 steps/sec)\n",
      "Epoch   0 Batch 7500/28124 Loss: 0.439832 acc: 0.796250 auc = 0.7763091921806335 (59.685089343269695 steps/sec)\n",
      "Epoch   0 Batch 7550/28124 Loss: 0.453674 acc: 0.794375 auc = 0.7745657563209534 (60.9338385506875 steps/sec)\n",
      "Epoch   0 Batch 7600/28124 Loss: 0.455357 acc: 0.791250 auc = 0.7723965644836426 (61.848131227680476 steps/sec)\n",
      "Epoch   0 Batch 7650/28124 Loss: 0.454355 acc: 0.782500 auc = 0.7860045433044434 (62.295060540944526 steps/sec)\n",
      "Epoch   0 Batch 7700/28124 Loss: 0.451298 acc: 0.795625 auc = 0.7964729070663452 (62.97880467865269 steps/sec)\n",
      "Epoch   0 Batch 7750/28124 Loss: 0.455017 acc: 0.789375 auc = 0.7950979471206665 (62.60691587607655 steps/sec)\n",
      "Epoch   0 Batch 7800/28124 Loss: 0.446577 acc: 0.793750 auc = 0.7918943762779236 (61.78399324284711 steps/sec)\n",
      "Epoch   0 Batch 7850/28124 Loss: 0.461633 acc: 0.781875 auc = 0.792320191860199 (62.78236545130573 steps/sec)\n",
      "Epoch   0 Batch 7900/28124 Loss: 0.442412 acc: 0.802500 auc = 0.8053841590881348 (57.630785194825755 steps/sec)\n",
      "Epoch   0 Batch 7950/28124 Loss: 0.424412 acc: 0.808125 auc = 0.8223968744277954 (54.77333136926276 steps/sec)\n",
      "Epoch   0 Batch 8000/28124 Loss: 0.464036 acc: 0.772500 auc = 0.792667031288147 (43.771653344448346 steps/sec)\n",
      "Epoch   0 Batch 8050/28124 Loss: 0.436885 acc: 0.798125 auc = 0.825197696685791 (58.80374320244911 steps/sec)\n",
      "Epoch   0 Batch 8100/28124 Loss: 0.454312 acc: 0.782500 auc = 0.7979679107666016 (58.94196028943267 steps/sec)\n",
      "Epoch   0 Batch 8150/28124 Loss: 0.427870 acc: 0.799375 auc = 0.7713707089424133 (60.44261422883754 steps/sec)\n",
      "Epoch   0 Batch 8200/28124 Loss: 0.453430 acc: 0.779375 auc = 0.8061293959617615 (56.35796457418288 steps/sec)\n",
      "Epoch   0 Batch 8250/28124 Loss: 0.453656 acc: 0.796250 auc = 0.7876889705657959 (58.85087197930575 steps/sec)\n",
      "Epoch   0 Batch 8300/28124 Loss: 0.444441 acc: 0.791250 auc = 0.8058198690414429 (58.5625540693976 steps/sec)\n",
      "Epoch   0 Batch 8350/28124 Loss: 0.448295 acc: 0.788125 auc = 0.8167329430580139 (62.45994528821969 steps/sec)\n",
      "Epoch   0 Batch 8400/28124 Loss: 0.456253 acc: 0.788750 auc = 0.7966703176498413 (62.20732492295097 steps/sec)\n",
      "Epoch   0 Batch 8450/28124 Loss: 0.429763 acc: 0.797500 auc = 0.8040820956230164 (61.614958804409746 steps/sec)\n",
      "Epoch   0 Batch 8500/28124 Loss: 0.454525 acc: 0.789375 auc = 0.7903976440429688 (62.012965891496705 steps/sec)\n",
      "Epoch   0 Batch 8550/28124 Loss: 0.447196 acc: 0.797500 auc = 0.8091052770614624 (62.66975938588685 steps/sec)\n",
      "Epoch   0 Batch 8600/28124 Loss: 0.444250 acc: 0.803750 auc = 0.8110285997390747 (62.233187500018545 steps/sec)\n",
      "Epoch   0 Batch 8650/28124 Loss: 0.452476 acc: 0.792500 auc = 0.7882412672042847 (61.92501680889884 steps/sec)\n",
      "Epoch   0 Batch 8700/28124 Loss: 0.469043 acc: 0.780000 auc = 0.7813477516174316 (61.77978883861237 steps/sec)\n",
      "Epoch   0 Batch 8750/28124 Loss: 0.476187 acc: 0.778125 auc = 0.795149564743042 (60.66842091864483 steps/sec)\n",
      "Epoch   0 Batch 8800/28124 Loss: 0.464555 acc: 0.773750 auc = 0.8098844289779663 (62.33689027154264 steps/sec)\n",
      "Epoch   0 Batch 8850/28124 Loss: 0.466136 acc: 0.770625 auc = 0.8151443600654602 (61.09662384774788 steps/sec)\n",
      "Epoch   0 Batch 8900/28124 Loss: 0.474044 acc: 0.769375 auc = 0.7983197569847107 (61.50675044117703 steps/sec)\n",
      "Epoch   0 Batch 8950/28124 Loss: 0.474762 acc: 0.771250 auc = 0.7781698703765869 (62.34474770936075 steps/sec)\n",
      "Epoch   0 Batch 9000/28124 Loss: 0.444279 acc: 0.792500 auc = 0.8147334456443787 (62.605420693159246 steps/sec)\n",
      "Epoch   0 Batch 9050/28124 Loss: 0.454096 acc: 0.792500 auc = 0.7992510199546814 (62.27922471697228 steps/sec)\n",
      "Epoch   0 Batch 9100/28124 Loss: 0.451609 acc: 0.785000 auc = 0.8167112469673157 (61.84842306799619 steps/sec)\n",
      "Epoch   0 Batch 9150/28124 Loss: 0.462390 acc: 0.790625 auc = 0.7943709492683411 (62.248113027493744 steps/sec)\n",
      "Epoch   0 Batch 9200/28124 Loss: 0.446255 acc: 0.791875 auc = 0.8155507445335388 (62.273639700205486 steps/sec)\n",
      "Epoch   0 Batch 9250/28124 Loss: 0.459386 acc: 0.783125 auc = 0.7876635193824768 (62.147541260516824 steps/sec)\n",
      "Epoch   0 Batch 9300/28124 Loss: 0.487618 acc: 0.768125 auc = 0.7849355936050415 (61.95318899906915 steps/sec)\n",
      "Epoch   0 Batch 9350/28124 Loss: 0.473978 acc: 0.778125 auc = 0.7580451965332031 (61.94488102689312 steps/sec)\n",
      "Epoch   0 Batch 9400/28124 Loss: 0.448035 acc: 0.790625 auc = 0.8148406147956848 (63.53377285701908 steps/sec)\n",
      "Epoch   0 Batch 9450/28124 Loss: 0.464729 acc: 0.782500 auc = 0.7912485003471375 (62.643457907214945 steps/sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch   0 Batch 9500/28124 Loss: 0.442713 acc: 0.783750 auc = 0.820462167263031 (62.71031251214794 steps/sec)\n",
      "Epoch   0 Batch 9550/28124 Loss: 0.455252 acc: 0.791875 auc = 0.7965091466903687 (61.55520561676223 steps/sec)\n",
      "Epoch   0 Batch 9600/28124 Loss: 0.470619 acc: 0.783125 auc = 0.7913939952850342 (62.86391054727206 steps/sec)\n",
      "Epoch   0 Batch 9650/28124 Loss: 0.457261 acc: 0.785625 auc = 0.7940799593925476 (62.69898833829527 steps/sec)\n",
      "Epoch   0 Batch 9700/28124 Loss: 0.461134 acc: 0.776875 auc = 0.7995164394378662 (62.19201319074987 steps/sec)\n",
      "Epoch   0 Batch 9750/28124 Loss: 0.447105 acc: 0.785000 auc = 0.8145182132720947 (62.613084260593666 steps/sec)\n",
      "Epoch   0 Batch 9800/28124 Loss: 0.418911 acc: 0.811875 auc = 0.8310021758079529 (58.678549634062094 steps/sec)\n",
      "Epoch   0 Batch 9850/28124 Loss: 0.452881 acc: 0.786250 auc = 0.8144449591636658 (62.479297970687206 steps/sec)\n",
      "Epoch   0 Batch 9900/28124 Loss: 0.454198 acc: 0.780000 auc = 0.7935832738876343 (62.64338305907557 steps/sec)\n",
      "Epoch   0 Batch 9950/28124 Loss: 0.460185 acc: 0.773750 auc = 0.7927352786064148 (61.85263681950072 steps/sec)\n",
      "Epoch   0 Batch 10000/28124 Loss: 0.471436 acc: 0.778125 auc = 0.7829059362411499 (61.94160602913673 steps/sec)\n",
      "Epoch   0 Batch 10050/28124 Loss: 0.455322 acc: 0.780000 auc = 0.8206356763839722 (60.88577298133436 steps/sec)\n",
      "Epoch   0 Batch 10100/28124 Loss: 0.483864 acc: 0.768750 auc = 0.7488680481910706 (61.41654295903196 steps/sec)\n",
      "Epoch   0 Batch 10150/28124 Loss: 0.441719 acc: 0.806250 auc = 0.7836735248565674 (62.46937822303139 steps/sec)\n",
      "Epoch   0 Batch 10200/28124 Loss: 0.465277 acc: 0.787500 auc = 0.7686946988105774 (61.532629441683945 steps/sec)\n",
      "Epoch   0 Batch 10250/28124 Loss: 0.461015 acc: 0.788125 auc = 0.8084845542907715 (62.45869893991712 steps/sec)\n",
      "Epoch   0 Batch 10300/28124 Loss: 0.469043 acc: 0.765625 auc = 0.7966353893280029 (62.53179661971109 steps/sec)\n",
      "Epoch   0 Batch 10350/28124 Loss: 0.441739 acc: 0.794375 auc = 0.8021208047866821 (62.7669947952364 steps/sec)\n",
      "Epoch   0 Batch 10400/28124 Loss: 0.455043 acc: 0.786875 auc = 0.794039785861969 (62.89354726585848 steps/sec)\n",
      "Epoch   0 Batch 10450/28124 Loss: 0.455039 acc: 0.791250 auc = 0.7865210771560669 (62.50428810331863 steps/sec)\n",
      "Epoch   0 Batch 10500/28124 Loss: 0.465763 acc: 0.768125 auc = 0.8061202764511108 (63.20080910459654 steps/sec)\n",
      "Epoch   0 Batch 10550/28124 Loss: 0.446720 acc: 0.789375 auc = 0.811830461025238 (61.77909725982281 steps/sec)\n",
      "Epoch   0 Batch 10600/28124 Loss: 0.451872 acc: 0.795625 auc = 0.8069923520088196 (61.29267013839975 steps/sec)\n",
      "Epoch   0 Batch 10650/28124 Loss: 0.454860 acc: 0.788125 auc = 0.7959719896316528 (62.722428656539286 steps/sec)\n",
      "Epoch   0 Batch 10700/28124 Loss: 0.437220 acc: 0.802500 auc = 0.809044599533081 (62.46180560209323 steps/sec)\n",
      "Epoch   0 Batch 10750/28124 Loss: 0.464050 acc: 0.784375 auc = 0.793779730796814 (62.31601467900813 steps/sec)\n",
      "Epoch   0 Batch 10800/28124 Loss: 0.461507 acc: 0.795000 auc = 0.7849079966545105 (63.04861396300815 steps/sec)\n",
      "Epoch   0 Batch 10850/28124 Loss: 0.449890 acc: 0.795625 auc = 0.7977651357650757 (61.759812089438924 steps/sec)\n",
      "Epoch   0 Batch 10900/28124 Loss: 0.457234 acc: 0.782500 auc = 0.7766482830047607 (62.66189470815777 steps/sec)\n",
      "Epoch   0 Batch 10950/28124 Loss: 0.457674 acc: 0.773750 auc = 0.8036417961120605 (61.78291933626916 steps/sec)\n",
      "Epoch   0 Batch 11000/28124 Loss: 0.447537 acc: 0.788125 auc = 0.8013442158699036 (61.59485331090194 steps/sec)\n",
      "Epoch   0 Batch 11050/28124 Loss: 0.438241 acc: 0.805625 auc = 0.8057296276092529 (62.15689848590605 steps/sec)\n",
      "Epoch   0 Batch 11100/28124 Loss: 0.446171 acc: 0.788750 auc = 0.8100581169128418 (62.27674647331886 steps/sec)\n",
      "Epoch   0 Batch 11150/28124 Loss: 0.463347 acc: 0.777500 auc = 0.791892409324646 (57.01404015106946 steps/sec)\n",
      "Epoch   0 Batch 11200/28124 Loss: 0.442787 acc: 0.790000 auc = 0.8010522723197937 (62.10493522246585 steps/sec)\n",
      "Epoch   0 Batch 11250/28124 Loss: 0.432446 acc: 0.804375 auc = 0.8107504844665527 (61.59972013371781 steps/sec)\n",
      "Epoch   0 Batch 11300/28124 Loss: 0.451900 acc: 0.793750 auc = 0.7992026805877686 (61.65928788537202 steps/sec)\n",
      "Epoch   0 Batch 11350/28124 Loss: 0.421883 acc: 0.804375 auc = 0.8153073191642761 (62.282849965935505 steps/sec)\n",
      "Epoch   0 Batch 11400/28124 Loss: 0.458994 acc: 0.790000 auc = 0.7940660119056702 (61.74181133870805 steps/sec)\n",
      "Epoch   0 Batch 11450/28124 Loss: 0.481029 acc: 0.765000 auc = 0.7795466780662537 (61.625170397261066 steps/sec)\n",
      "Epoch   0 Batch 11500/28124 Loss: 0.434780 acc: 0.801250 auc = 0.8115435242652893 (61.37514852470339 steps/sec)\n",
      "Epoch   0 Batch 11550/28124 Loss: 0.453098 acc: 0.773125 auc = 0.8184996247291565 (61.863365323745846 steps/sec)\n",
      "Epoch   0 Batch 11600/28124 Loss: 0.476167 acc: 0.778125 auc = 0.7870073914527893 (61.29134454754075 steps/sec)\n",
      "Epoch   0 Batch 11650/28124 Loss: 0.445954 acc: 0.796875 auc = 0.8165672421455383 (61.97785154292091 steps/sec)\n",
      "Epoch   0 Batch 11700/28124 Loss: 0.434814 acc: 0.804375 auc = 0.807212769985199 (62.44638694777514 steps/sec)\n",
      "Epoch   0 Batch 11750/28124 Loss: 0.448436 acc: 0.785625 auc = 0.7987885475158691 (61.946454612667765 steps/sec)\n",
      "Epoch   0 Batch 11800/28124 Loss: 0.438007 acc: 0.800625 auc = 0.8037763833999634 (60.22868584616463 steps/sec)\n",
      "Epoch   0 Batch 11850/28124 Loss: 0.445722 acc: 0.783125 auc = 0.8248666524887085 (61.76110345575007 steps/sec)\n",
      "Epoch   0 Batch 11900/28124 Loss: 0.427982 acc: 0.811875 auc = 0.8083577752113342 (60.76205801848922 steps/sec)\n",
      "Epoch   0 Batch 11950/28124 Loss: 0.469516 acc: 0.781250 auc = 0.7943037152290344 (61.70264598958928 steps/sec)\n",
      "Epoch   0 Batch 12000/28124 Loss: 0.456584 acc: 0.776875 auc = 0.8097236752510071 (61.9031735695854 steps/sec)\n",
      "Epoch   0 Batch 12050/28124 Loss: 0.438594 acc: 0.795000 auc = 0.7936880588531494 (62.51093936669711 steps/sec)\n",
      "Epoch   0 Batch 12100/28124 Loss: 0.426890 acc: 0.812500 auc = 0.8130538463592529 (54.737833395018775 steps/sec)\n",
      "Epoch   0 Batch 12150/28124 Loss: 0.434517 acc: 0.796250 auc = 0.8010492920875549 (59.46165724100896 steps/sec)\n",
      "Epoch   0 Batch 12200/28124 Loss: 0.461003 acc: 0.771875 auc = 0.7946287393569946 (61.18557198820024 steps/sec)\n",
      "Epoch   0 Batch 12250/28124 Loss: 0.453722 acc: 0.786250 auc = 0.8055379390716553 (61.890075021152356 steps/sec)\n",
      "Epoch   0 Batch 12300/28124 Loss: 0.443284 acc: 0.789375 auc = 0.7962502837181091 (61.93130759496848 steps/sec)\n",
      "Epoch   0 Batch 12350/28124 Loss: 0.454022 acc: 0.793125 auc = 0.8006427884101868 (59.767365906514314 steps/sec)\n",
      "Epoch   0 Batch 12400/28124 Loss: 0.478442 acc: 0.764375 auc = 0.7802958488464355 (53.55210903920639 steps/sec)\n",
      "Epoch   0 Batch 12450/28124 Loss: 0.458603 acc: 0.778125 auc = 0.7972372174263 (61.140388214783414 steps/sec)\n",
      "Epoch   0 Batch 12500/28124 Loss: 0.463455 acc: 0.786250 auc = 0.7971588969230652 (62.768103184838814 steps/sec)\n",
      "Epoch   0 Batch 12550/28124 Loss: 0.454318 acc: 0.788125 auc = 0.8027842044830322 (62.7184144307094 steps/sec)\n",
      "Epoch   0 Batch 12600/28124 Loss: 0.434795 acc: 0.806250 auc = 0.8254992961883545 (58.099741465193105 steps/sec)\n",
      "Epoch   0 Batch 12650/28124 Loss: 0.458181 acc: 0.784375 auc = 0.8087424635887146 (62.698351006389565 steps/sec)\n",
      "Epoch   0 Batch 12700/28124 Loss: 0.471987 acc: 0.779375 auc = 0.7801153659820557 (63.37039593201819 steps/sec)\n",
      "Epoch   0 Batch 12750/28124 Loss: 0.468226 acc: 0.773750 auc = 0.7910072207450867 (62.97458737668746 steps/sec)\n",
      "Epoch   0 Batch 12800/28124 Loss: 0.457030 acc: 0.796875 auc = 0.7737489342689514 (62.52016404912888 steps/sec)\n",
      "Epoch   0 Batch 12850/28124 Loss: 0.456874 acc: 0.781875 auc = 0.8071485757827759 (62.99316286862747 steps/sec)\n",
      "Epoch   0 Batch 12900/28124 Loss: 0.450137 acc: 0.792500 auc = 0.7909595966339111 (62.39291777167811 steps/sec)\n",
      "Epoch   0 Batch 12950/28124 Loss: 0.485274 acc: 0.771875 auc = 0.7800012230873108 (62.516734758365146 steps/sec)\n",
      "Epoch   0 Batch 13000/28124 Loss: 0.475895 acc: 0.773125 auc = 0.7959210872650146 (62.62540597552979 steps/sec)\n",
      "Epoch   0 Batch 13050/28124 Loss: 0.444805 acc: 0.787500 auc = 0.8219009637832642 (61.48058679362548 steps/sec)\n",
      "Epoch   0 Batch 13100/28124 Loss: 0.453787 acc: 0.791250 auc = 0.7886864542961121 (57.75545573242628 steps/sec)\n",
      "Epoch   0 Batch 13150/28124 Loss: 0.469813 acc: 0.775000 auc = 0.7901657223701477 (61.99128046612172 steps/sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch   0 Batch 13200/28124 Loss: 0.454636 acc: 0.781250 auc = 0.7966324090957642 (60.68211358683134 steps/sec)\n",
      "Epoch   0 Batch 13250/28124 Loss: 0.437188 acc: 0.803750 auc = 0.7910498976707458 (60.22536495878724 steps/sec)\n",
      "Epoch   0 Batch 13300/28124 Loss: 0.445096 acc: 0.807500 auc = 0.7823901176452637 (62.172745882502916 steps/sec)\n",
      "Epoch   0 Batch 13350/28124 Loss: 0.454795 acc: 0.801250 auc = 0.7835655808448792 (63.313823301119186 steps/sec)\n",
      "Epoch   0 Batch 13400/28124 Loss: 0.456120 acc: 0.783125 auc = 0.8006329536437988 (63.410902498214526 steps/sec)\n",
      "Epoch   0 Batch 13450/28124 Loss: 0.440400 acc: 0.805000 auc = 0.8123332858085632 (62.738565775287164 steps/sec)\n",
      "Epoch   0 Batch 13500/28124 Loss: 0.463874 acc: 0.780625 auc = 0.7888399362564087 (61.95104774463721 steps/sec)\n",
      "Epoch   0 Batch 13550/28124 Loss: 0.440108 acc: 0.801875 auc = 0.8022376298904419 (62.633093142725905 steps/sec)\n",
      "Epoch   0 Batch 13600/28124 Loss: 0.441128 acc: 0.788125 auc = 0.8045130968093872 (62.93076467190301 steps/sec)\n",
      "Epoch   0 Batch 13650/28124 Loss: 0.448044 acc: 0.793750 auc = 0.8023619651794434 (59.28666658374108 steps/sec)\n",
      "Epoch   0 Batch 13700/28124 Loss: 0.438825 acc: 0.791875 auc = 0.8073831796646118 (59.029858161278604 steps/sec)\n",
      "Epoch   0 Batch 13750/28124 Loss: 0.441032 acc: 0.789375 auc = 0.811820387840271 (58.9176016851966 steps/sec)\n",
      "Epoch   0 Batch 13800/28124 Loss: 0.445288 acc: 0.798750 auc = 0.7988641858100891 (61.78668727448536 steps/sec)\n",
      "Epoch   0 Batch 13850/28124 Loss: 0.471954 acc: 0.778125 auc = 0.7887497544288635 (49.110421122366944 steps/sec)\n",
      "Epoch   0 Batch 13900/28124 Loss: 0.451176 acc: 0.790625 auc = 0.8041397333145142 (52.591781932207915 steps/sec)\n",
      "Epoch   0 Batch 13950/28124 Loss: 0.443112 acc: 0.796250 auc = 0.7921798825263977 (60.49308822091386 steps/sec)\n",
      "Epoch   0 Batch 14000/28124 Loss: 0.448175 acc: 0.784375 auc = 0.7957170605659485 (58.699572618592114 steps/sec)\n",
      "Epoch   0 Batch 14050/28124 Loss: 0.442098 acc: 0.801875 auc = 0.8044275641441345 (54.5999392857273 steps/sec)\n",
      "Epoch   0 Batch 14100/28124 Loss: 0.460533 acc: 0.786250 auc = 0.802829384803772 (52.38393316124739 steps/sec)\n",
      "Epoch   0 Batch 14150/28124 Loss: 0.439318 acc: 0.795625 auc = 0.7874031662940979 (54.95399083275597 steps/sec)\n",
      "Epoch   0 Batch 14200/28124 Loss: 0.427098 acc: 0.809375 auc = 0.8204686641693115 (46.30177828332427 steps/sec)\n",
      "Epoch   0 Batch 14250/28124 Loss: 0.436935 acc: 0.797500 auc = 0.8042580485343933 (57.92191134529839 steps/sec)\n",
      "Epoch   0 Batch 14300/28124 Loss: 0.466065 acc: 0.776250 auc = 0.7921728491783142 (60.2036844166149 steps/sec)\n",
      "Epoch   0 Batch 14350/28124 Loss: 0.435132 acc: 0.804375 auc = 0.8034749031066895 (63.031521290907406 steps/sec)\n",
      "Epoch   0 Batch 14400/28124 Loss: 0.464640 acc: 0.773125 auc = 0.7898743152618408 (63.85246977275101 steps/sec)\n",
      "Epoch   0 Batch 14450/28124 Loss: 0.434213 acc: 0.798125 auc = 0.7974359393119812 (60.129166553174045 steps/sec)\n",
      "Epoch   0 Batch 14500/28124 Loss: 0.460787 acc: 0.788750 auc = 0.7922384142875671 (62.347861581725226 steps/sec)\n",
      "Epoch   0 Batch 14550/28124 Loss: 0.456799 acc: 0.786875 auc = 0.8048086762428284 (56.347924964083155 steps/sec)\n",
      "Epoch   0 Batch 14600/28124 Loss: 0.449866 acc: 0.797500 auc = 0.8128567337989807 (51.96241137668853 steps/sec)\n",
      "Epoch   0 Batch 14650/28124 Loss: 0.422878 acc: 0.816875 auc = 0.8158383965492249 (59.10647187276993 steps/sec)\n",
      "Epoch   0 Batch 14700/28124 Loss: 0.450493 acc: 0.791250 auc = 0.8011093139648438 (59.49330245314781 steps/sec)\n",
      "Epoch   0 Batch 14750/28124 Loss: 0.444626 acc: 0.789375 auc = 0.7962580323219299 (46.475775952911505 steps/sec)\n",
      "Epoch   0 Batch 14800/28124 Loss: 0.463268 acc: 0.781875 auc = 0.7416574358940125 (58.87666303288011 steps/sec)\n",
      "Epoch   0 Batch 14850/28124 Loss: 0.466123 acc: 0.771875 auc = 0.8185417056083679 (56.94604502131588 steps/sec)\n",
      "Epoch   0 Batch 14900/28124 Loss: 0.458325 acc: 0.786250 auc = 0.800341010093689 (57.791775644171764 steps/sec)\n",
      "Epoch   0 Batch 14950/28124 Loss: 0.438137 acc: 0.808750 auc = 0.8052346706390381 (63.8252441131034 steps/sec)\n",
      "Epoch   0 Batch 15000/28124 Loss: 0.455201 acc: 0.780000 auc = 0.7957392334938049 (64.03022911512485 steps/sec)\n",
      "Epoch   0 Batch 15050/28124 Loss: 0.435797 acc: 0.810625 auc = 0.7969112396240234 (57.29029706021274 steps/sec)\n",
      "Epoch   0 Batch 15100/28124 Loss: 0.452156 acc: 0.788750 auc = 0.8077182769775391 (61.94259398080953 steps/sec)\n",
      "Epoch   0 Batch 15150/28124 Loss: 0.457395 acc: 0.790000 auc = 0.8024517893791199 (64.53095061016869 steps/sec)\n",
      "Epoch   0 Batch 15200/28124 Loss: 0.450572 acc: 0.788750 auc = 0.8062310814857483 (63.990665424172136 steps/sec)\n",
      "Epoch   0 Batch 15250/28124 Loss: 0.470713 acc: 0.776875 auc = 0.772807776927948 (49.25176560770912 steps/sec)\n",
      "Epoch   0 Batch 15300/28124 Loss: 0.438764 acc: 0.796875 auc = 0.7938993573188782 (59.540596816441436 steps/sec)\n",
      "Epoch   0 Batch 15350/28124 Loss: 0.456875 acc: 0.795625 auc = 0.8023958802223206 (45.007453483865234 steps/sec)\n",
      "Epoch   0 Batch 15400/28124 Loss: 0.461522 acc: 0.786250 auc = 0.7759501934051514 (58.5043935093564 steps/sec)\n",
      "Epoch   0 Batch 15450/28124 Loss: 0.457822 acc: 0.786250 auc = 0.8068101406097412 (54.4437495602889 steps/sec)\n",
      "Epoch   0 Batch 15500/28124 Loss: 0.471113 acc: 0.783125 auc = 0.7830619812011719 (58.06187612924517 steps/sec)\n",
      "Epoch   0 Batch 15550/28124 Loss: 0.438167 acc: 0.794375 auc = 0.8107424974441528 (64.06929369410764 steps/sec)\n",
      "Epoch   0 Batch 15600/28124 Loss: 0.447276 acc: 0.796250 auc = 0.8078411817550659 (63.72973984834819 steps/sec)\n",
      "Epoch   0 Batch 15650/28124 Loss: 0.444032 acc: 0.801250 auc = 0.8039191961288452 (58.27920133546128 steps/sec)\n",
      "Epoch   0 Batch 15700/28124 Loss: 0.455711 acc: 0.794375 auc = 0.7824851274490356 (48.65568540033859 steps/sec)\n",
      "Epoch   0 Batch 15750/28124 Loss: 0.460332 acc: 0.779375 auc = 0.7965502142906189 (54.66399717863509 steps/sec)\n",
      "Epoch   0 Batch 15800/28124 Loss: 0.468554 acc: 0.778750 auc = 0.799598217010498 (53.790851601104464 steps/sec)\n",
      "Epoch   0 Batch 15850/28124 Loss: 0.440051 acc: 0.798125 auc = 0.8075923323631287 (48.63775454116608 steps/sec)\n",
      "Epoch   0 Batch 15900/28124 Loss: 0.449209 acc: 0.794375 auc = 0.81219083070755 (54.633223241169574 steps/sec)\n",
      "Epoch   0 Batch 15950/28124 Loss: 0.451999 acc: 0.790625 auc = 0.7925662994384766 (53.71164902532076 steps/sec)\n",
      "Epoch   0 Batch 16000/28124 Loss: 0.459573 acc: 0.783125 auc = 0.793404757976532 (51.56961159364124 steps/sec)\n",
      "Epoch   0 Batch 16050/28124 Loss: 0.452991 acc: 0.789375 auc = 0.8060687780380249 (40.677821448362984 steps/sec)\n",
      "Epoch   0 Batch 16100/28124 Loss: 0.452780 acc: 0.795625 auc = 0.7969861626625061 (52.402218974425224 steps/sec)\n",
      "Epoch   0 Batch 16150/28124 Loss: 0.475365 acc: 0.770625 auc = 0.7832290530204773 (56.13896827427881 steps/sec)\n",
      "Epoch   0 Batch 16200/28124 Loss: 0.444145 acc: 0.799375 auc = 0.7928199768066406 (59.71333412869412 steps/sec)\n",
      "Epoch   0 Batch 16250/28124 Loss: 0.454881 acc: 0.790000 auc = 0.8025251030921936 (58.72774731144705 steps/sec)\n",
      "Epoch   0 Batch 16300/28124 Loss: 0.438000 acc: 0.793125 auc = 0.8050934672355652 (46.20636244358198 steps/sec)\n",
      "Epoch   0 Batch 16350/28124 Loss: 0.451474 acc: 0.782500 auc = 0.8017243146896362 (63.25157069381371 steps/sec)\n",
      "Epoch   0 Batch 16400/28124 Loss: 0.432476 acc: 0.800625 auc = 0.8131887316703796 (63.172632839676645 steps/sec)\n",
      "Epoch   0 Batch 16450/28124 Loss: 0.413711 acc: 0.809375 auc = 0.8209113478660583 (56.12730902842828 steps/sec)\n",
      "Epoch   0 Batch 16500/28124 Loss: 0.450123 acc: 0.795000 auc = 0.7910131216049194 (62.250533558531146 steps/sec)\n",
      "Epoch   0 Batch 16550/28124 Loss: 0.453416 acc: 0.787500 auc = 0.8093578815460205 (52.205633966202974 steps/sec)\n",
      "Epoch   0 Batch 16600/28124 Loss: 0.448124 acc: 0.796250 auc = 0.7961676120758057 (64.44221424238718 steps/sec)\n",
      "Epoch   0 Batch 16650/28124 Loss: 0.466657 acc: 0.780000 auc = 0.7785947322845459 (64.4202216300483 steps/sec)\n",
      "Epoch   0 Batch 16700/28124 Loss: 0.424611 acc: 0.809375 auc = 0.8127645254135132 (64.31645943465115 steps/sec)\n",
      "Epoch   0 Batch 16750/28124 Loss: 0.457148 acc: 0.780000 auc = 0.792266309261322 (63.87753945835041 steps/sec)\n",
      "Epoch   0 Batch 16800/28124 Loss: 0.446620 acc: 0.788750 auc = 0.8021714091300964 (64.48884227086364 steps/sec)\n",
      "Epoch   0 Batch 16850/28124 Loss: 0.443243 acc: 0.790625 auc = 0.7996813058853149 (64.90042205426978 steps/sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch   0 Batch 16900/28124 Loss: 0.456361 acc: 0.800625 auc = 0.797105610370636 (64.46057600894083 steps/sec)\n",
      "Epoch   0 Batch 16950/28124 Loss: 0.454647 acc: 0.790625 auc = 0.7938568592071533 (63.744365020527724 steps/sec)\n",
      "Epoch   0 Batch 17000/28124 Loss: 0.468144 acc: 0.769375 auc = 0.7747938632965088 (58.48786499625309 steps/sec)\n",
      "Epoch   0 Batch 17050/28124 Loss: 0.452899 acc: 0.788125 auc = 0.7941279411315918 (58.01715766963325 steps/sec)\n",
      "Epoch   0 Batch 17100/28124 Loss: 0.458888 acc: 0.785625 auc = 0.7958393096923828 (61.15991268502303 steps/sec)\n",
      "Epoch   0 Batch 17150/28124 Loss: 0.458667 acc: 0.782500 auc = 0.7885387539863586 (64.34574448337365 steps/sec)\n",
      "Epoch   0 Batch 17200/28124 Loss: 0.440135 acc: 0.804375 auc = 0.8107438087463379 (62.344692107323795 steps/sec)\n",
      "Epoch   0 Batch 17250/28124 Loss: 0.467394 acc: 0.778125 auc = 0.7836556434631348 (64.93269410588866 steps/sec)\n",
      "Epoch   0 Batch 17300/28124 Loss: 0.455962 acc: 0.776875 auc = 0.8118547201156616 (64.4683041515255 steps/sec)\n",
      "Epoch   0 Batch 17350/28124 Loss: 0.471103 acc: 0.768750 auc = 0.7919900417327881 (63.61145529852297 steps/sec)\n",
      "Epoch   0 Batch 17400/28124 Loss: 0.454523 acc: 0.793125 auc = 0.8095510601997375 (64.08940205590746 steps/sec)\n",
      "Epoch   0 Batch 17450/28124 Loss: 0.441639 acc: 0.796875 auc = 0.7857595682144165 (64.28255052956462 steps/sec)\n",
      "Epoch   0 Batch 17500/28124 Loss: 0.446834 acc: 0.783750 auc = 0.8076186180114746 (64.91331898761133 steps/sec)\n",
      "Epoch   0 Batch 17550/28124 Loss: 0.448531 acc: 0.798750 auc = 0.7899004220962524 (64.34756087645029 steps/sec)\n",
      "Epoch   0 Batch 17600/28124 Loss: 0.442384 acc: 0.797500 auc = 0.8101756572723389 (62.67367373499953 steps/sec)\n",
      "Epoch   0 Batch 17650/28124 Loss: 0.449495 acc: 0.799375 auc = 0.7978461384773254 (64.42526811195728 steps/sec)\n",
      "Epoch   0 Batch 17700/28124 Loss: 0.442926 acc: 0.793750 auc = 0.8191699385643005 (56.242717069218585 steps/sec)\n",
      "Epoch   0 Batch 17750/28124 Loss: 0.458528 acc: 0.780625 auc = 0.7937651872634888 (63.1486266997252 steps/sec)\n",
      "Epoch   0 Batch 17800/28124 Loss: 0.455473 acc: 0.800000 auc = 0.7846615314483643 (63.27767896071607 steps/sec)\n",
      "Epoch   0 Batch 17850/28124 Loss: 0.430450 acc: 0.800000 auc = 0.8181905150413513 (61.95932075997925 steps/sec)\n",
      "Epoch   0 Batch 17900/28124 Loss: 0.484327 acc: 0.770000 auc = 0.7683391571044922 (63.7904927724557 steps/sec)\n",
      "Epoch   0 Batch 17950/28124 Loss: 0.449543 acc: 0.796250 auc = 0.8034464120864868 (65.43629145090169 steps/sec)\n",
      "Epoch   0 Batch 18000/28124 Loss: 0.453675 acc: 0.795000 auc = 0.7946317791938782 (65.66332529169843 steps/sec)\n",
      "Epoch   0 Batch 18050/28124 Loss: 0.457310 acc: 0.777500 auc = 0.7971289753913879 (63.91018481412688 steps/sec)\n",
      "Epoch   0 Batch 18100/28124 Loss: 0.452048 acc: 0.788125 auc = 0.8083679676055908 (64.53434627783516 steps/sec)\n",
      "Epoch   0 Batch 18150/28124 Loss: 0.437963 acc: 0.794375 auc = 0.8161636590957642 (64.81126824635645 steps/sec)\n",
      "Epoch   0 Batch 18200/28124 Loss: 0.436230 acc: 0.796250 auc = 0.8104350566864014 (61.96638751803159 steps/sec)\n",
      "Epoch   0 Batch 18250/28124 Loss: 0.442165 acc: 0.795000 auc = 0.8160539269447327 (62.867717263866695 steps/sec)\n",
      "Epoch   0 Batch 18300/28124 Loss: 0.465891 acc: 0.778750 auc = 0.8056900501251221 (63.66440573721347 steps/sec)\n",
      "Epoch   0 Batch 18350/28124 Loss: 0.491639 acc: 0.763750 auc = 0.7604988217353821 (64.40251572327044 steps/sec)\n",
      "Epoch   0 Batch 18400/28124 Loss: 0.448438 acc: 0.803125 auc = 0.7586283087730408 (61.99690658745512 steps/sec)\n",
      "Epoch   0 Batch 18450/28124 Loss: 0.446795 acc: 0.791875 auc = 0.7958008050918579 (60.33351630584258 steps/sec)\n",
      "Epoch   0 Batch 18500/28124 Loss: 0.448838 acc: 0.793125 auc = 0.8041253685951233 (59.10452287337076 steps/sec)\n",
      "Epoch   0 Batch 18550/28124 Loss: 0.443146 acc: 0.800625 auc = 0.8151522278785706 (61.10445657250697 steps/sec)\n",
      "Epoch   0 Batch 18600/28124 Loss: 0.450163 acc: 0.798750 auc = 0.8174119591712952 (49.37531916817211 steps/sec)\n",
      "Epoch   0 Batch 18650/28124 Loss: 0.450224 acc: 0.801250 auc = 0.7885878682136536 (59.07966358866181 steps/sec)\n",
      "Epoch   0 Batch 18700/28124 Loss: 0.482528 acc: 0.765000 auc = 0.7695437073707581 (63.78048209318635 steps/sec)\n",
      "Epoch   0 Batch 18750/28124 Loss: 0.432117 acc: 0.802500 auc = 0.8068787455558777 (63.28426668597949 steps/sec)\n",
      "Epoch   0 Batch 18800/28124 Loss: 0.441365 acc: 0.786250 auc = 0.80743008852005 (63.839271852787626 steps/sec)\n",
      "Epoch   0 Batch 18850/28124 Loss: 0.461531 acc: 0.785625 auc = 0.7924404740333557 (64.2136994606379 steps/sec)\n",
      "Epoch   0 Batch 18900/28124 Loss: 0.463371 acc: 0.773750 auc = 0.7843816876411438 (64.46164594893914 steps/sec)\n",
      "Epoch   0 Batch 18950/28124 Loss: 0.433401 acc: 0.805625 auc = 0.8006770610809326 (63.11791329304754 steps/sec)\n",
      "Epoch   0 Batch 19000/28124 Loss: 0.455120 acc: 0.788750 auc = 0.8006490468978882 (64.09943158286612 steps/sec)\n",
      "Epoch   0 Batch 19050/28124 Loss: 0.443597 acc: 0.790625 auc = 0.8139156103134155 (63.809513957053255 steps/sec)\n",
      "Epoch   0 Batch 19100/28124 Loss: 0.439877 acc: 0.796250 auc = 0.8035094738006592 (62.77832475744387 steps/sec)\n",
      "Epoch   0 Batch 19150/28124 Loss: 0.450772 acc: 0.788750 auc = 0.8153212070465088 (63.59073940936156 steps/sec)\n",
      "Epoch   0 Batch 19200/28124 Loss: 0.458999 acc: 0.781875 auc = 0.7796297669410706 (63.98640913673121 steps/sec)\n",
      "Epoch   0 Batch 19250/28124 Loss: 0.461036 acc: 0.781875 auc = 0.7842946648597717 (63.853850135493104 steps/sec)\n",
      "Epoch   0 Batch 19300/28124 Loss: 0.479392 acc: 0.768125 auc = 0.7779900431632996 (64.09541547750833 steps/sec)\n",
      "Epoch   0 Batch 19350/28124 Loss: 0.448695 acc: 0.797500 auc = 0.7986128330230713 (63.00767904886632 steps/sec)\n",
      "Epoch   0 Batch 19400/28124 Loss: 0.452489 acc: 0.785625 auc = 0.7899925708770752 (63.69857479833284 steps/sec)\n",
      "Epoch   0 Batch 19450/28124 Loss: 0.458774 acc: 0.781875 auc = 0.8007607460021973 (61.57960650047936 steps/sec)\n",
      "Epoch   0 Batch 19500/28124 Loss: 0.440792 acc: 0.796250 auc = 0.8021488785743713 (64.35818488088154 steps/sec)\n",
      "Epoch   0 Batch 19550/28124 Loss: 0.458299 acc: 0.775625 auc = 0.7836421728134155 (63.24197636001105 steps/sec)\n",
      "Epoch   0 Batch 19600/28124 Loss: 0.447321 acc: 0.792500 auc = 0.7898711562156677 (61.24539634172162 steps/sec)\n",
      "Epoch   0 Batch 19650/28124 Loss: 0.448660 acc: 0.790000 auc = 0.8006008267402649 (62.8824773600509 steps/sec)\n",
      "Epoch   0 Batch 19700/28124 Loss: 0.449018 acc: 0.795625 auc = 0.8002771735191345 (54.69507683488422 steps/sec)\n",
      "Epoch   0 Batch 19750/28124 Loss: 0.450730 acc: 0.782500 auc = 0.8032932877540588 (54.45911759252575 steps/sec)\n",
      "Epoch   0 Batch 19800/28124 Loss: 0.457010 acc: 0.788125 auc = 0.7971508502960205 (57.67251480965187 steps/sec)\n",
      "Epoch   0 Batch 19850/28124 Loss: 0.451623 acc: 0.795000 auc = 0.8165310621261597 (62.556045050212724 steps/sec)\n",
      "Epoch   0 Batch 19900/28124 Loss: 0.457202 acc: 0.785625 auc = 0.8020426034927368 (64.56309469090927 steps/sec)\n",
      "Epoch   0 Batch 19950/28124 Loss: 0.436771 acc: 0.807500 auc = 0.8138174414634705 (63.92479550577552 steps/sec)\n",
      "Epoch   0 Batch 20000/28124 Loss: 0.449577 acc: 0.790625 auc = 0.7897359728813171 (64.47028602504167 steps/sec)\n",
      "Epoch   0 Batch 20050/28124 Loss: 0.431728 acc: 0.795625 auc = 0.8147503733634949 (63.60383475726447 steps/sec)\n",
      "Epoch   0 Batch 20100/28124 Loss: 0.461797 acc: 0.777500 auc = 0.7945725321769714 (64.10307589932664 steps/sec)\n",
      "Epoch   0 Batch 20150/28124 Loss: 0.438644 acc: 0.787500 auc = 0.8210570812225342 (65.01375668264767 steps/sec)\n",
      "Epoch   0 Batch 20200/28124 Loss: 0.482059 acc: 0.762500 auc = 0.7714433073997498 (63.35954038809966 steps/sec)\n",
      "Epoch   0 Batch 20250/28124 Loss: 0.451756 acc: 0.790625 auc = 0.8078172206878662 (63.5502531825854 steps/sec)\n",
      "Epoch   0 Batch 20300/28124 Loss: 0.465358 acc: 0.780000 auc = 0.788983166217804 (63.993926357697376 steps/sec)\n",
      "Epoch   0 Batch 20350/28124 Loss: 0.458823 acc: 0.783750 auc = 0.8008294105529785 (64.73054967902517 steps/sec)\n",
      "Epoch   0 Batch 20400/28124 Loss: 0.452913 acc: 0.792500 auc = 0.7868511080741882 (64.33514432176898 steps/sec)\n",
      "Epoch   0 Batch 20450/28124 Loss: 0.432369 acc: 0.796875 auc = 0.8127684593200684 (64.54068184119342 steps/sec)\n",
      "Epoch   0 Batch 20500/28124 Loss: 0.457228 acc: 0.788750 auc = 0.7903011441230774 (62.5343884389244 steps/sec)\n",
      "Epoch   0 Batch 20550/28124 Loss: 0.452550 acc: 0.792500 auc = 0.8041450381278992 (63.96554590194186 steps/sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch   0 Batch 20600/28124 Loss: 0.443049 acc: 0.795000 auc = 0.8002539277076721 (64.36142412270566 steps/sec)\n",
      "Epoch   0 Batch 20650/28124 Loss: 0.449586 acc: 0.788125 auc = 0.8089896440505981 (63.72503410120941 steps/sec)\n",
      "Epoch   0 Batch 20700/28124 Loss: 0.446929 acc: 0.790625 auc = 0.8229220509529114 (63.926101052616175 steps/sec)\n",
      "Epoch   0 Batch 20750/28124 Loss: 0.462561 acc: 0.785000 auc = 0.7943018078804016 (64.00738366425327 steps/sec)\n",
      "Epoch   0 Batch 20800/28124 Loss: 0.472014 acc: 0.783750 auc = 0.7839899659156799 (64.88726924841731 steps/sec)\n",
      "Epoch   0 Batch 20850/28124 Loss: 0.444957 acc: 0.797500 auc = 0.7932684421539307 (61.85117744663105 steps/sec)\n",
      "Epoch   0 Batch 20900/28124 Loss: 0.455342 acc: 0.785000 auc = 0.8064648509025574 (64.10609355020837 steps/sec)\n",
      "Epoch   0 Batch 20950/28124 Loss: 0.464922 acc: 0.788750 auc = 0.7875370979309082 (63.779085504006815 steps/sec)\n",
      "Epoch   0 Batch 21000/28124 Loss: 0.470045 acc: 0.783125 auc = 0.7783563733100891 (64.04067035980798 steps/sec)\n",
      "Epoch   0 Batch 21050/28124 Loss: 0.458638 acc: 0.792500 auc = 0.8014690279960632 (63.95351035715615 steps/sec)\n",
      "Epoch   0 Batch 21100/28124 Loss: 0.447823 acc: 0.790625 auc = 0.8122889995574951 (64.26586550071033 steps/sec)\n",
      "Epoch   0 Batch 21150/28124 Loss: 0.434407 acc: 0.802500 auc = 0.8162720203399658 (63.432441481991425 steps/sec)\n",
      "Epoch   0 Batch 21200/28124 Loss: 0.447015 acc: 0.780625 auc = 0.8016969561576843 (64.75879329484731 steps/sec)\n",
      "Epoch   0 Batch 21250/28124 Loss: 0.455431 acc: 0.787500 auc = 0.7913665175437927 (64.49050809732348 steps/sec)\n",
      "Epoch   0 Batch 21300/28124 Loss: 0.457537 acc: 0.793125 auc = 0.7934163808822632 (64.20166863257909 steps/sec)\n",
      "Epoch   0 Batch 21350/28124 Loss: 0.466521 acc: 0.778750 auc = 0.7791944146156311 (64.26198604479137 steps/sec)\n",
      "Epoch   0 Batch 21400/28124 Loss: 0.456666 acc: 0.799375 auc = 0.8003963232040405 (64.63447032854862 steps/sec)\n",
      "Epoch   0 Batch 21450/28124 Loss: 0.435318 acc: 0.803750 auc = 0.8042507767677307 (60.402156462792725 steps/sec)\n",
      "Epoch   0 Batch 21500/28124 Loss: 0.454530 acc: 0.783750 auc = 0.8111048936843872 (59.28624757691741 steps/sec)\n",
      "Epoch   0 Batch 21550/28124 Loss: 0.455655 acc: 0.785000 auc = 0.7849252820014954 (63.1491781415493 steps/sec)\n",
      "Epoch   0 Batch 21600/28124 Loss: 0.437328 acc: 0.789375 auc = 0.7960774898529053 (64.5348626094813 steps/sec)\n",
      "Epoch   0 Batch 21650/28124 Loss: 0.440851 acc: 0.780625 auc = 0.7957215309143066 (65.23625977267574 steps/sec)\n",
      "Epoch   0 Batch 21700/28124 Loss: 0.452090 acc: 0.785625 auc = 0.8029183149337769 (61.43669417788164 steps/sec)\n",
      "Epoch   0 Batch 21750/28124 Loss: 0.481268 acc: 0.770000 auc = 0.7754220366477966 (62.635206976883104 steps/sec)\n",
      "Epoch   0 Batch 21800/28124 Loss: 0.426505 acc: 0.803750 auc = 0.8124534487724304 (65.22927969637769 steps/sec)\n",
      "Epoch   0 Batch 21850/28124 Loss: 0.443008 acc: 0.799375 auc = 0.7925281524658203 (64.5780651264308 steps/sec)\n",
      "Epoch   0 Batch 21900/28124 Loss: 0.460064 acc: 0.780000 auc = 0.7836049795150757 (65.018654691948 steps/sec)\n",
      "Epoch   0 Batch 21950/28124 Loss: 0.470963 acc: 0.761250 auc = 0.7896726131439209 (63.15889650702709 steps/sec)\n",
      "Epoch   0 Batch 22000/28124 Loss: 0.460591 acc: 0.781875 auc = 0.7916481494903564 (62.894735579345394 steps/sec)\n",
      "Epoch   0 Batch 22050/28124 Loss: 0.456265 acc: 0.782500 auc = 0.7852545380592346 (62.63859315015835 steps/sec)\n",
      "Epoch   0 Batch 22100/28124 Loss: 0.442581 acc: 0.786875 auc = 0.8195425271987915 (64.50707188649055 steps/sec)\n",
      "Epoch   0 Batch 22150/28124 Loss: 0.440499 acc: 0.796250 auc = 0.7935316562652588 (64.04870891803704 steps/sec)\n",
      "Epoch   0 Batch 22200/28124 Loss: 0.433912 acc: 0.815625 auc = 0.7894790172576904 (65.39042456730704 steps/sec)\n",
      "Epoch   0 Batch 22250/28124 Loss: 0.461377 acc: 0.781875 auc = 0.7986534833908081 (64.68596576673224 steps/sec)\n",
      "Epoch   0 Batch 22300/28124 Loss: 0.449237 acc: 0.787500 auc = 0.8115089535713196 (64.6744554108581 steps/sec)\n",
      "Epoch   0 Batch 22350/28124 Loss: 0.439815 acc: 0.801875 auc = 0.8148598670959473 (63.67051364141314 steps/sec)\n",
      "Epoch   0 Batch 22400/28124 Loss: 0.469811 acc: 0.781875 auc = 0.79322350025177 (64.70682251128198 steps/sec)\n",
      "Epoch   0 Batch 22450/28124 Loss: 0.459724 acc: 0.781250 auc = 0.7869312763214111 (64.83964250191768 steps/sec)\n",
      "Epoch   0 Batch 22500/28124 Loss: 0.457506 acc: 0.786250 auc = 0.7821172475814819 (65.63272623028188 steps/sec)\n",
      "Epoch   0 Batch 22550/28124 Loss: 0.450053 acc: 0.781250 auc = 0.812041163444519 (63.24609603541766 steps/sec)\n",
      "Epoch   0 Batch 22600/28124 Loss: 0.461381 acc: 0.782500 auc = 0.7960406541824341 (57.888511550501924 steps/sec)\n",
      "Epoch   0 Batch 22650/28124 Loss: 0.467323 acc: 0.778750 auc = 0.7856358289718628 (62.55013043008822 steps/sec)\n",
      "Epoch   0 Batch 22700/28124 Loss: 0.431672 acc: 0.796875 auc = 0.8008123636245728 (60.373638812743586 steps/sec)\n",
      "Epoch   0 Batch 22750/28124 Loss: 0.440602 acc: 0.796875 auc = 0.8060401678085327 (63.15085154121175 steps/sec)\n",
      "Epoch   0 Batch 22800/28124 Loss: 0.436772 acc: 0.804375 auc = 0.8020567893981934 (64.44659080118484 steps/sec)\n",
      "Epoch   0 Batch 22850/28124 Loss: 0.458339 acc: 0.780625 auc = 0.7897117137908936 (61.64399104301598 steps/sec)\n",
      "Epoch   0 Batch 22900/28124 Loss: 0.464228 acc: 0.774375 auc = 0.7808589339256287 (63.9823876606232 steps/sec)\n",
      "Epoch   0 Batch 22950/28124 Loss: 0.435175 acc: 0.790625 auc = 0.814128577709198 (63.46686132058399 steps/sec)\n",
      "Epoch   0 Batch 23000/28124 Loss: 0.463804 acc: 0.778125 auc = 0.7908840775489807 (61.79111109277777 steps/sec)\n",
      "Epoch   0 Batch 23050/28124 Loss: 0.437076 acc: 0.800000 auc = 0.80218505859375 (64.04730055766282 steps/sec)\n",
      "Epoch   0 Batch 23100/28124 Loss: 0.445652 acc: 0.799375 auc = 0.8048392534255981 (64.06134781171666 steps/sec)\n",
      "Epoch   0 Batch 23150/28124 Loss: 0.457281 acc: 0.783750 auc = 0.795513927936554 (62.011278906930094 steps/sec)\n",
      "Epoch   0 Batch 23200/28124 Loss: 0.447015 acc: 0.780000 auc = 0.8134334087371826 (60.01891159857957 steps/sec)\n",
      "Epoch   0 Batch 23250/28124 Loss: 0.454904 acc: 0.786250 auc = 0.8040047287940979 (59.788443506296716 steps/sec)\n",
      "Epoch   0 Batch 23300/28124 Loss: 0.444383 acc: 0.796875 auc = 0.8057389855384827 (63.6067670025823 steps/sec)\n",
      "Epoch   0 Batch 23350/28124 Loss: 0.444502 acc: 0.791875 auc = 0.8024841547012329 (62.54112071410401 steps/sec)\n",
      "Epoch   0 Batch 23400/28124 Loss: 0.445940 acc: 0.788125 auc = 0.8048632144927979 (63.70563749471816 steps/sec)\n",
      "Epoch   0 Batch 23450/28124 Loss: 0.449758 acc: 0.796250 auc = 0.7935569286346436 (64.9402141230548 steps/sec)\n",
      "Epoch   0 Batch 23500/28124 Loss: 0.458294 acc: 0.782500 auc = 0.8095422983169556 (61.76172187564146 steps/sec)\n",
      "Epoch   0 Batch 23550/28124 Loss: 0.456495 acc: 0.795000 auc = 0.788069486618042 (64.80798356709798 steps/sec)\n",
      "Epoch   0 Batch 23600/28124 Loss: 0.437426 acc: 0.798125 auc = 0.8012818694114685 (62.14159315111195 steps/sec)\n",
      "Epoch   0 Batch 23650/28124 Loss: 0.451761 acc: 0.790000 auc = 0.8005366325378418 (57.28084563015972 steps/sec)\n",
      "Epoch   0 Batch 23700/28124 Loss: 0.428053 acc: 0.808750 auc = 0.8039114475250244 (60.708480594523664 steps/sec)\n",
      "Epoch   0 Batch 23750/28124 Loss: 0.459711 acc: 0.785000 auc = 0.7903663516044617 (56.32520898172907 steps/sec)\n",
      "Epoch   0 Batch 23800/28124 Loss: 0.446863 acc: 0.786875 auc = 0.8082953095436096 (51.90054329520557 steps/sec)\n",
      "Epoch   0 Batch 23850/28124 Loss: 0.451390 acc: 0.791875 auc = 0.8003572225570679 (55.84656808167228 steps/sec)\n",
      "Epoch   0 Batch 23900/28124 Loss: 0.472832 acc: 0.782500 auc = 0.7674029469490051 (61.24194450836533 steps/sec)\n",
      "Epoch   0 Batch 23950/28124 Loss: 0.462550 acc: 0.785625 auc = 0.7960346341133118 (61.86380330093364 steps/sec)\n",
      "Epoch   0 Batch 24000/28124 Loss: 0.471449 acc: 0.778125 auc = 0.7875738739967346 (63.166258590605985 steps/sec)\n",
      "Epoch   0 Batch 24050/28124 Loss: 0.438806 acc: 0.799375 auc = 0.8186569809913635 (64.01973264464449 steps/sec)\n",
      "Epoch   0 Batch 24100/28124 Loss: 0.451759 acc: 0.783750 auc = 0.7971348762512207 (64.42718796168319 steps/sec)\n",
      "Epoch   0 Batch 24150/28124 Loss: 0.430556 acc: 0.803125 auc = 0.8104220628738403 (64.89142536046631 steps/sec)\n",
      "Epoch   0 Batch 24200/28124 Loss: 0.451209 acc: 0.798750 auc = 0.7926589846611023 (64.94079729875773 steps/sec)\n",
      "Epoch   0 Batch 24250/28124 Loss: 0.461804 acc: 0.776250 auc = 0.7906429767608643 (64.25989881561381 steps/sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch   0 Batch 24300/28124 Loss: 0.452220 acc: 0.791250 auc = 0.8087559342384338 (64.68604557552682 steps/sec)\n",
      "Epoch   0 Batch 24350/28124 Loss: 0.438979 acc: 0.805625 auc = 0.814507246017456 (64.0587844130646 steps/sec)\n",
      "Epoch   0 Batch 24400/28124 Loss: 0.473170 acc: 0.773125 auc = 0.786251425743103 (65.30892901742254 steps/sec)\n",
      "Epoch   0 Batch 24450/28124 Loss: 0.427439 acc: 0.801875 auc = 0.8107969164848328 (62.10763892282301 steps/sec)\n",
      "Epoch   0 Batch 24500/28124 Loss: 0.445392 acc: 0.808125 auc = 0.8020789623260498 (57.27973482251671 steps/sec)\n",
      "Epoch   0 Batch 24550/28124 Loss: 0.454355 acc: 0.791250 auc = 0.7932253479957581 (61.340142560889646 steps/sec)\n",
      "Epoch   0 Batch 24600/28124 Loss: 0.451938 acc: 0.793125 auc = 0.8028668165206909 (57.57322690333395 steps/sec)\n",
      "Epoch   0 Batch 24650/28124 Loss: 0.453851 acc: 0.791875 auc = 0.7953385710716248 (57.213789460876185 steps/sec)\n",
      "Epoch   0 Batch 24700/28124 Loss: 0.433724 acc: 0.805625 auc = 0.7989079356193542 (54.72392125754128 steps/sec)\n",
      "Epoch   0 Batch 24750/28124 Loss: 0.452448 acc: 0.795000 auc = 0.7888617515563965 (58.696894635934896 steps/sec)\n",
      "Epoch   0 Batch 24800/28124 Loss: 0.466051 acc: 0.781875 auc = 0.7840022444725037 (52.9633591842466 steps/sec)\n",
      "Epoch   0 Batch 24850/28124 Loss: 0.463482 acc: 0.771250 auc = 0.8157079815864563 (55.220310964979376 steps/sec)\n",
      "Epoch   0 Batch 24900/28124 Loss: 0.433695 acc: 0.796875 auc = 0.8096487522125244 (50.239849746543115 steps/sec)\n",
      "Epoch   0 Batch 24950/28124 Loss: 0.432449 acc: 0.815625 auc = 0.8121629357337952 (57.97489595269459 steps/sec)\n",
      "Epoch   0 Batch 25000/28124 Loss: 0.449122 acc: 0.794375 auc = 0.8015946745872498 (52.56201843572535 steps/sec)\n",
      "Epoch   0 Batch 25050/28124 Loss: 0.453772 acc: 0.783125 auc = 0.8066673874855042 (59.7144053052845 steps/sec)\n",
      "Epoch   0 Batch 25100/28124 Loss: 0.450314 acc: 0.788125 auc = 0.8038292527198792 (58.49054025221346 steps/sec)\n",
      "Epoch   0 Batch 25150/28124 Loss: 0.454773 acc: 0.792500 auc = 0.7944936156272888 (58.44152731727409 steps/sec)\n",
      "Epoch   0 Batch 25200/28124 Loss: 0.471801 acc: 0.774375 auc = 0.7682094573974609 (60.429238370159744 steps/sec)\n",
      "Epoch   0 Batch 25250/28124 Loss: 0.460008 acc: 0.778750 auc = 0.7970142364501953 (59.52727922997664 steps/sec)\n",
      "Epoch   0 Batch 25300/28124 Loss: 0.431967 acc: 0.789375 auc = 0.8181441426277161 (59.866886476688 steps/sec)\n",
      "Epoch   0 Batch 25350/28124 Loss: 0.447381 acc: 0.790000 auc = 0.7972800731658936 (53.82785318920389 steps/sec)\n",
      "Epoch   0 Batch 25400/28124 Loss: 0.449160 acc: 0.800625 auc = 0.7981875538825989 (61.83709803639426 steps/sec)\n",
      "Epoch   0 Batch 25450/28124 Loss: 0.457931 acc: 0.800000 auc = 0.789700448513031 (61.43631622088285 steps/sec)\n",
      "Epoch   0 Batch 25500/28124 Loss: 0.453573 acc: 0.785625 auc = 0.8050395250320435 (61.522249961129674 steps/sec)\n",
      "Epoch   0 Batch 25550/28124 Loss: 0.440794 acc: 0.790000 auc = 0.7958106398582458 (60.79159588838579 steps/sec)\n",
      "Epoch   0 Batch 25600/28124 Loss: 0.426599 acc: 0.812500 auc = 0.8169633746147156 (61.59622824609449 steps/sec)\n",
      "Epoch   0 Batch 25650/28124 Loss: 0.414465 acc: 0.802500 auc = 0.8181445598602295 (60.62471597774769 steps/sec)\n",
      "Epoch   0 Batch 25700/28124 Loss: 0.462613 acc: 0.780000 auc = 0.7976257801055908 (53.887286348669925 steps/sec)\n",
      "Epoch   0 Batch 25750/28124 Loss: 0.473798 acc: 0.773750 auc = 0.7853924036026001 (60.879303988364974 steps/sec)\n",
      "Epoch   0 Batch 25800/28124 Loss: 0.442104 acc: 0.778125 auc = 0.8210601806640625 (59.92660737115285 steps/sec)\n",
      "Epoch   0 Batch 25850/28124 Loss: 0.458823 acc: 0.788750 auc = 0.7955701947212219 (51.00926321401712 steps/sec)\n",
      "Epoch   0 Batch 25900/28124 Loss: 0.438903 acc: 0.806875 auc = 0.8064703941345215 (50.390625187719706 steps/sec)\n",
      "Epoch   0 Batch 25950/28124 Loss: 0.472691 acc: 0.780625 auc = 0.780036985874176 (52.1612518986986 steps/sec)\n",
      "Epoch   0 Batch 26000/28124 Loss: 0.465329 acc: 0.787500 auc = 0.7849608659744263 (48.18464801793249 steps/sec)\n",
      "Epoch   0 Batch 26050/28124 Loss: 0.450229 acc: 0.791250 auc = 0.795360803604126 (50.87463090061705 steps/sec)\n",
      "Epoch   0 Batch 26100/28124 Loss: 0.438259 acc: 0.801875 auc = 0.8101526498794556 (52.703477348068795 steps/sec)\n",
      "Epoch   0 Batch 26150/28124 Loss: 0.454101 acc: 0.784375 auc = 0.7803518772125244 (59.562022235444644 steps/sec)\n",
      "Epoch   0 Batch 26200/28124 Loss: 0.448551 acc: 0.795000 auc = 0.7913796305656433 (53.18600921316787 steps/sec)\n",
      "Epoch   0 Batch 26250/28124 Loss: 0.421992 acc: 0.798125 auc = 0.8142984509468079 (43.58731025721924 steps/sec)\n",
      "Epoch   0 Batch 26300/28124 Loss: 0.471113 acc: 0.773750 auc = 0.7835894227027893 (56.11175088081305 steps/sec)\n",
      "Epoch   0 Batch 26350/28124 Loss: 0.458856 acc: 0.784375 auc = 0.8078953623771667 (58.31337790447421 steps/sec)\n",
      "Epoch   0 Batch 26400/28124 Loss: 0.447635 acc: 0.791875 auc = 0.7927599549293518 (58.528068551857636 steps/sec)\n",
      "Epoch   0 Batch 26450/28124 Loss: 0.463295 acc: 0.785000 auc = 0.77568519115448 (60.490505813388346 steps/sec)\n",
      "Epoch   0 Batch 26500/28124 Loss: 0.462504 acc: 0.774375 auc = 0.787111759185791 (60.063966208519986 steps/sec)\n",
      "Epoch   0 Batch 26550/28124 Loss: 0.448628 acc: 0.796875 auc = 0.7943283319473267 (60.500889128400296 steps/sec)\n",
      "Epoch   0 Batch 26600/28124 Loss: 0.448545 acc: 0.804375 auc = 0.8000862002372742 (58.92947212630056 steps/sec)\n",
      "Epoch   0 Batch 26650/28124 Loss: 0.433875 acc: 0.795000 auc = 0.8098054528236389 (60.33138140794665 steps/sec)\n",
      "Epoch   0 Batch 26700/28124 Loss: 0.454648 acc: 0.795000 auc = 0.7948163747787476 (60.32147260015889 steps/sec)\n",
      "Epoch   0 Batch 26750/28124 Loss: 0.474915 acc: 0.766875 auc = 0.7975556254386902 (60.68852317644495 steps/sec)\n",
      "Epoch   0 Batch 26800/28124 Loss: 0.463142 acc: 0.779375 auc = 0.779121994972229 (60.94357766052325 steps/sec)\n",
      "Epoch   0 Batch 26850/28124 Loss: 0.450546 acc: 0.786875 auc = 0.8078746795654297 (58.079901850141454 steps/sec)\n",
      "Epoch   0 Batch 26900/28124 Loss: 0.434568 acc: 0.800625 auc = 0.8136915564537048 (60.30662416081521 steps/sec)\n",
      "Epoch   0 Batch 26950/28124 Loss: 0.462497 acc: 0.785000 auc = 0.7902752161026001 (59.747579785870165 steps/sec)\n",
      "Epoch   0 Batch 27000/28124 Loss: 0.445835 acc: 0.792500 auc = 0.8205391764640808 (59.99693314016694 steps/sec)\n",
      "Epoch   0 Batch 27050/28124 Loss: 0.429720 acc: 0.808750 auc = 0.8026888966560364 (60.66076976032489 steps/sec)\n",
      "Epoch   0 Batch 27100/28124 Loss: 0.458072 acc: 0.795000 auc = 0.7907409071922302 (60.078179049790805 steps/sec)\n",
      "Epoch   0 Batch 27150/28124 Loss: 0.447563 acc: 0.790625 auc = 0.7965973019599915 (58.47062851509308 steps/sec)\n",
      "Epoch   0 Batch 27200/28124 Loss: 0.456363 acc: 0.793125 auc = 0.791647732257843 (60.93267006667823 steps/sec)\n",
      "Epoch   0 Batch 27250/28124 Loss: 0.464061 acc: 0.792500 auc = 0.7867456078529358 (61.59394878175001 steps/sec)\n",
      "Epoch   0 Batch 27300/28124 Loss: 0.460081 acc: 0.788125 auc = 0.7876635789871216 (60.421142582697065 steps/sec)\n",
      "Epoch   0 Batch 27350/28124 Loss: 0.449518 acc: 0.799375 auc = 0.7956199645996094 (60.31536581479664 steps/sec)\n",
      "Epoch   0 Batch 27400/28124 Loss: 0.447331 acc: 0.787500 auc = 0.8130139112472534 (60.89717660266006 steps/sec)\n",
      "Epoch   0 Batch 27450/28124 Loss: 0.457708 acc: 0.785000 auc = 0.7952845692634583 (59.40183262756872 steps/sec)\n",
      "Epoch   0 Batch 27500/28124 Loss: 0.460987 acc: 0.768125 auc = 0.7969415783882141 (60.88621490259928 steps/sec)\n",
      "Epoch   0 Batch 27550/28124 Loss: 0.451725 acc: 0.791250 auc = 0.7959526777267456 (60.683307599534245 steps/sec)\n",
      "Epoch   0 Batch 27600/28124 Loss: 0.461321 acc: 0.781875 auc = 0.7817792296409607 (59.60541065350308 steps/sec)\n",
      "Epoch   0 Batch 27650/28124 Loss: 0.480813 acc: 0.768125 auc = 0.7921594381332397 (60.97924936698997 steps/sec)\n",
      "Epoch   0 Batch 27700/28124 Loss: 0.446916 acc: 0.791250 auc = 0.8047346472740173 (62.073629913473205 steps/sec)\n",
      "Epoch   0 Batch 27750/28124 Loss: 0.459928 acc: 0.790625 auc = 0.7771673798561096 (60.43967033514927 steps/sec)\n",
      "Epoch   0 Batch 27800/28124 Loss: 0.449493 acc: 0.796250 auc = 0.7962015271186829 (60.58065395788029 steps/sec)\n",
      "Epoch   0 Batch 27850/28124 Loss: 0.445107 acc: 0.786250 auc = 0.8242310881614685 (60.98900299949921 steps/sec)\n",
      "Epoch   0 Batch 27900/28124 Loss: 0.456076 acc: 0.791250 auc = 0.8002626299858093 (59.99499362760314 steps/sec)\n",
      "Epoch   0 Batch 27950/28124 Loss: 0.442921 acc: 0.792500 auc = 0.8029370903968811 (59.80024117967601 steps/sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch   0 Batch 28000/28124 Loss: 0.436451 acc: 0.801875 auc = 0.7901540994644165 (60.00261508894879 steps/sec)\n",
      "Epoch   0 Batch 28050/28124 Loss: 0.434431 acc: 0.800000 auc = 0.802182137966156 (61.289141327426 steps/sec)\n",
      "Epoch   0 Batch 28100/28124 Loss: 0.452012 acc: 0.793125 auc = 0.7950044274330139 (61.463811224524186 steps/sec)\n",
      "\n",
      "Train time for epoch #1 : 475.47269773483276\n",
      "Model test set loss: 0.468333  acc: 0.781570  auc = 0.7790644764900208 prediction = 0.2547439634799957\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "         0.0       0.80      0.93      0.86     74423\n",
      "         1.0       0.64      0.34      0.44     25577\n",
      "\n",
      "   micro avg       0.78      0.78      0.78    100000\n",
      "   macro avg       0.72      0.64      0.65    100000\n",
      "weighted avg       0.76      0.78      0.76    100000\n",
      "\n",
      "best loss = 0.4683328866958618\n"
     ]
    }
   ],
   "source": [
    "ctr_net=ctr_network()\n",
    "ctr_net.training((train_X, train_y), (test_X, test_y), False, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1的recall和f1-score都很小，对用户点击的预测很差。0的recall已经快100%了，数据不均衡导致网络更倾向于预测成0。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 327,
   "metadata": {},
   "outputs": [],
   "source": [
    "# %matplotlib inline\n",
    "# %config InlineBackend.figure_format = 'retina'\n",
    "# import matplotlib.pyplot as plt\n",
    "# from sklearn.model_selection import train_test_split\n",
    "# import time\n",
    "# import datetime\n",
    "# from sklearn.metrics import log_loss\n",
    "# from sklearn.learning_curve import learning_curve\n",
    "# from sklearn import metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 查看loss曲线"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 下采样的loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 250,
       "width": 373
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(ctr_net.losses['train'], label='Training loss')\n",
    "plt.legend()\n",
    "_ = plt.ylim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 250,
       "width": 373
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(ctr_net.losses['test'], label='Test loss')\n",
    "plt.legend()\n",
    "_ = plt.ylim()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 全数据的loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PPtnlSOB1q3ftr//7Kcf00n333as33nhDCxYs0HnnnediZNER6ntj4MCBWr58+XJr7cBIzseYdQAAAIQtKyur2WNLly7VO++8o2OOOUaDBg1yIarEwzAYAAAAhO3kk0/WGWecoaN+8EN16XKwMrdu0sLZ30qShg8fXl/rHZHhpwgAAICw3XHHHZo+fbrSVoxXeWmpevY6VL/61ZV6+OGHdO6557odXsIgWQeABDBlVZZGztuqPwzqq9+f5a1KBvFuc06JvlmbrV+d+j0d36e72+EAnjF06FANHTq02Zj1Dh0oo+wkxqwDQAK4+5MVWrO7UP+YuEaVNaEvL47WWWt1/dspeumbDfrDu0vcDgdAEiJZB4AEU1njczuEhFFeXav80ipJ0u795S5HAyAZkawjoRjuvAEAgChxo+Q5yToAAGjGBHo/fD7u1AB16pJ1E8PeQZJ1AADQTJcuXSRJpaWlLkcCeEfd+6Hu/RELJOsAAKCZnj17SpKys7NVXFwsn8/nyhAAwG3WWvl8PhUXFys7O1vSgfdHLFC6EQAANNO7d2+VlpaqrKxMu3btcjsceFhN1YEKVOuL9iT8/LFu3bqpd+/eMTsfyToAAGimQ4cOOu6445Sfn6/i4mJVVlbSs44Wbcopqf/7Kd8/REaJl60bY9SlSxf17NlTvXv3VocOsRucQrIOAEAMFJZVa+GWPJ33wz7q1bWT2+GEpEOHDurTp4/69OnjdijwsF+OmVb/94ynf6KunTu6GE3iIVkHACAG/jQ6VSt2+Fd6XP/M5Tq4EwkNgLYxwRRAvYLSKpVXsfol4LTKmtr6RF2S3luwzcVoAMQTknXUq6gmSUtmKVv2adDQWTp76CztLapwOxxEIPFGiyael77Z4HYIAOIEyTokSU9OWatTnvhGr8yI7y8QkpT2u2HkYlXV+FRYXq1/TU53OxwAACCSdUgqq6rR6EWZqvFZvfndZrfDgQfszC93O4S44fNRHQMAED0k61B1DckG0B7frd+rM5/7VreMSiVpBwBEBck6ALTTn0cvU35plWZvyNW0NXvcDgcAkIBI1gHAAdvySt0OwXU+n9WugrIW963NKtSkFbuZyA4AYSJZBwBEzFqr695O0fn/nq1Xm0xUzyup1ODhC3XvZyv1FvNiACAsJOsAEKeqa336PG2Xvlmb7XYoWrFzv9K2F0iS3miSkI+ct1XVtf4x/W/NJlkH4JyaWp/bIUQdK5gCQJwat2ynHv3CG2U2Sytrgu5j6i2AaPhs6Q499eU6/fzko/TGDae7HU7U0LMOAHHKK4k6ALjh4c/XqKyqVlNWZWn1rv1tPyFOkayDlYQAAIAjrEv30nKKKl05bywwDAYAACSFqhqfxi3bqYM7ddRvTv++OnagtwreR7KOhGIMH7wAnGM9MODeWiufFYmlAz5esl1PfrlOktS1U0f96rTvuRwR0DaGwQCImR37yrRoS56sFzIgxLVkqdeeV1KpX7w2Txe8OFub9ha7HU7cq0vUJemJKcz5QHwgWUdCIQn0rr1FFfrZK3N048gl+iBlu9vhII49OWWtTnniG738zYa2D45zT0xZq805Jdq9v1y3j01zOxwALiBZB9DMuj1Fuv3DNO0pLG93G00vnF78eoNqfP7HnpiyNqL4kLzKq2o1elGmanw2KWq2Lw/UrpekLbmskgskI8eSdWPMscaY940xWcaYSmNMpjHmdWPMYWG2c74xZnLg+RXGmB3GmOnGmMudihVA275em60Hx69u33PT9+jMZ7/VvZ+uqH+soiY5hi0guqp9sV0AhWkwANzmSLJujDlJUpqkWySlSnpN0lZJ90hKMcYcHmI7/ydpvqRLAtvXJM2VdKGkr4wxjzoRL4DQLNic167n3T52ufaVVmnSyiwt2tK+NoBEYqiRC6CdnOpZHyHpSEl3W2sHW2v/Ya39mfzJ9o8kPddWA8aYTpKGSqqQNNBaO8Ra+4i1doikMyVVSnrUGNPFoZgBxMDO/LKYn9Naq805JfL5mMOQaJiWAiDZRJysB3rVL5WUKWl4k91PSCqVNMQY072NpnpL6iVpo7W20awha22GpI2SukrqEWnMABLb/eNX6eevztWtHyxzOxRXOFnC1Fqrr9OzNW7pTlUylAkAYs6JOusXB7YzrLWNBhNaa4uNMQvlT+bPljSrlXZyJOVK6m+M6Wet3VS3wxjTX1I/SSuttfsciBlAApu4fLckadb6HBVXVKvnwZ1cjih+pWzZV1+FpKSyRn8+/wSXI0K4qmp8GjZro8qqanXfL/rrEN4PQFxxYhjMjwLbjUH21yXd/VtrxPpLR9wZiCnNGDPGGDPUGPOB/OPh10q6zoF4gYitzSrUazM3KjOP6gxeF+P5iAmnYeWep6euC3pczMZkR3EYTF5JpWoTcOjUBymZGj57i0YtzNSrM4J9VQPwKid61nsFtoVB9tc9fmhbDVlrxxtjsiR9IumPDXbtlTRK/kmrbTLGBCtGOyCU5yN+xWIF05panwYPX6jqWqvPl+/Sgod/FvVzAvEsHqZWfrxkhx6btEb9juypaXefr4M6Bu/L2pJboicmr1Xfw7vp2atPUQePryz69rwDX52jF2Xqyav+n4vRAAiXp+qsG2NukvSt/JVgTpbULbCdJektSZ+6Fx3gl1Ncqepaf+/broL21yEH4B3//GKNfFbasLdYU1ZltXrsrR8s04LNefp4yQ5NWL4rRhEC8YFJ4M5zome9rue8V5D9dY/vb62RwLj09yWtljSkwfj39caYIfIPt7nOGHORtXZOa21ZawcGOUeapDNae24yoo4wgHhhozkOJiC/tKrV/VsbLE40d2Ourj/zuGiHBCCJOdGzXle5JdiY9H6BbVsD5S6V1EnS3BYmqvokzQv8s8VEHACQeIoqqjX0qwwNn705IceTt4W+FABO9KzPDmwvNcZ0aJhoG2N6SjpPUpmkxW20U1c//Ygg++seb73LAwCQMF6dsVGjF2VKkvr06KzL/t/R7gYEJJGK6lrN3ZirnxzfW727d3Y7nJCs2FGgfSVVunjAkero8fkkoYq4Z91au0XSDEnHy1/NpaGnJHWX9KG1tv6+oTFmgDGm6WTP+YHttcaY0xruMMb8WNK18tcB+C7SmAH47d5frqHTM/Ttur1uhwK0qC5Rl6S3525lPCwQQw+MX6X//TBNvxmxMC4WmVufXaTfjFikv36wTBPSdrodjmOc6FmXpDskLZL0hjHmEkkZkgbJX4N9o6RHmxyfEdjWX/JYa1ONMaMk3SJpqTHmC0nb5b8IGCyps6TXrbVrBcARd328XCt27G9ULSJe7cwvk7VS38O7uRZDSWWNpq3O0v8cd6gGHH2Ia3EAgBOmrt4jSdq+r0xrs4p06rHBpid6w6NfpNf//eHP1+h3P+nrYjTOcSRZt9ZuMcacKelpSZdLukLSHknDJD1lrS0Isam/yD82/U+SLpPUU1KRpAWSRlprqQYDOGjFjlbnfceNFTsKdM1/FkmSJtx+jmtxPD89Qx8v2aGunToq9dFLkmoxplhM/IS3zFibrTkbc/Xn847XD4/s6XY4iDJfHNzWqomD3v/2cKpnXdbanfL3iodybIuDiAILI40O/AGAkNw+Nq1+eMRfxyxzLY6Pl+yQJJVX12rSyiwNOfsHrsUC1InGqN3c4krd9qF/SZPvMnK0+J+XhN1Grc+qqLxah8XJWGh4W2Km6X6eqrMORGrVzsToKUZ4cosr6/9eUFbdeGdizC9CQCJ/IceThp+12UUVYT+/qsanS1+bq588960mrdjtZGhAwiFZR8jySio1auE2bdxb7HYoQbVVHxmIFq4JgAMqqmtb3f9J6g5tyS1Vjc/q3s9Wtvs8OcXhXygA8YZkHSG7f9wqPfXlOl0zYlGzD+Kc4oqkrIEMAF4X60/md+dv1alPfqP7WknC97ajN76pB8ev0lnPzdIjE1dH3FYoNu4t1h/fT9XQrzJk42D8NhIHyTpCNndjriR/xYuGt0A/WrJdg56fpV8Om6eaWl+wpwOIQ15b4TjWSZJTp4vFz7GiulZ7Csujf6I2PDstQ9W1Vl+s2K1teaVtP6Edamp9Gp+2S5L0SerOmHQW/en9VM3bmKu3527VrIycqJ9PkoorqrVgU56q+W5NaiTriNijX6TLWmnj3hJ9wdhDICkZBgJFhQkxyy+prNH5//5O577wnSav9M7ncFF5ddsHtUPT1Pznr85VeVXrQ28ilVV44G7Ags15UT2X5L8w/c2IRbrpvSV6aEJs7h7Am0jW4SjGjMNzYtQRm6ijwNy82x8XvYke+b0Pn71ZeSVVsla659P2jwGPV9vySvX2vC2SJJ/POjLMJhwfpGTqF6/O1fhlzi3EszarSJtzSiQprjrCIn1LWGu1OaeEobUNkKyD/jDAAZ8v3+V2CAnnnk9XNHuMr++WNayI1FSyfMbvKiiXtVa/eydFg56fpTdnbYrJeStravWvyWu1KadEDzrYA56syeqTU9bq56/O1Q0jF7sdimeQrCMiTXu+vDa+NRrc+j/uLarQNSMW6tr/LGr1izkRrd61Xze9uyTol2+oQwWiaUd+mdsh1HP/p+GM6WuyG/07nlOXaCwoszO/TIOHL9SNIxeruCI6w03izfIdBVqa6V+H8ZWZG1s91qlfSWVN63eAfD6rmev26rv1e5mYGoIxKdslSanb8rU1tyTk5yXK515LHFsUCcmnorpWl7wy1+0wXLdy5379+LhDo36ef05co+WBFUefnLJWw/9wRtTP6RXX/idFVbU+Ldicp/P79dHpfQ9zOyQgZPmlVbp6+ALH271/3CqtZG2JRooqatwOoZmZGXv1v4EFpMb8+Sxd2P8IlyOKH1XxMBQuBuhZR7u9t2Cbdu9vXHkgHieZ7Sks1+/eTtHN76eqqB29U2uzCqMQVXOz1h+oPjBz3d6YnNMrGn5gr9gRX8lJeVWtXv92o0bM2ayqNnrg0LZYdEw6fafmmanrtDPf+SotqZn5jrcZKx64GRYzdYm6JN36gXsrLCN+kayj3XJiPIEnWh6asFpLtuVr7sZcvfj1+qidp7rWp/vHrdKQ95Zoxz7vDJlIeC4nBf+du0Wvf7tJL369QZ+k7nA3GI/ZVVCm12Zu1PIdBW6HEpQTSeXqXfF1gRkLyTaUr04yXKMkw/8x1kjWkfTmbzpQguubtdHrsR6zKFOfL9+l+Zvy9LcWJs4htkoqa5S+uzBqY0jrvrCGNRhn/8qMDVE5V7y69YM0DZu1SdeMWKSyKu8NX3Db1tySZncvE8H941Zp3DImZCeLpZn5uvLN+Xrqy7WNHt+ZX6Yrhs3Xb0YspJJcG0jW0aKcogrllSRnz0e0zGgwdGUV40xdVVlTq5+9PEdXvrlAI+ZscTucpJWxp6j+7+uyilo58gAb19NMw3PHR8vdDsExucWVKiyrVlWNLy4rJ8VqYmitz2rG2mzN3ZjruVd6e+O57r8pSt9dpFELM7Voy4HOsfvHrdK6PUVasWO/nm6SyKMxknU0k7a9QOe+8J3OGTpL67ND+wIN166CMo1dvF05xYkxlAbBeXEew8Tlu5UTuA3/0jf0dsOb1mcXux2CI9K25+vcF2bprOe/1aac+Pw/LdvevqFavjDLL36Vvke3fZimm99P1ZKt+9p1Ti9bu/tATtFwzsW8Tc4sMuW9bxtnkKyjmb+OWaoan1V1rdVdH7c8XCPYBKxQxndaa/XH91L12KR0nfXcLD00YVXUV55DYgv3A7q0kiEXyaDWZ5W2PV8V1Xy+uOlP7y9Vda1VZY1/3k48KixrX2nMz8JcJKnhd+7Qr6I3hwrxhWQdzRQ0+FDaE4XxkrklldqaV1r/73HLdmnEnM2Onwfe4PSwhWSqIuEF0fp5h9vjWC+Mpz0ycbV++58U/WbEIupbu8RKKm5wcbyrIPHG4LfmkYlrYnKeAhfHfO8vY7x5tJGsJ7jC8mq9NnOjxi3d6ekvq3EOLtGM+FNSWaPpa/Y0m2S0Ibs44qoR6/cU6fFJ6Vq42ZnbrHDGl6uzon6OukmMGXuKEmZICVqXjNfyL3+zQac/M1N3fuzOHIdnp2W4ct5kwqJICe7fX6/Xx0v85eKOObSrzu/Xx+WIEk/67iJd/vrfaCTMAAAgAElEQVQ8ndCnu9668Qx17JCMXxeRuevj5ZqzIVcDju6pr+75qYwxmrxyt+75dKU6HxRZn8Lv3vEvWf3h4u1a9/Rl6tY58T/23Lj7EO45J6TFdpJhTW3onRXh/FdCuXPUWt32ict36YsVu3XbBSfqp/1YLAfhe2u2/870tNV79OgV5Trm0K4xPT8FE6KPnvUEV5eoS9LI+Vujfj4vLPsea5+k7tD67GJ9lZ6tj6mj3S5zNuRK8k+o21Pon3R8z6crJcnRhYTqbsFHY+l3RJ+1iVULpqiiWn8ft0rzN+VpyHupbocT99yqYOalb73yJJ6f8X8fpWlPYWIOsyJZR7u19KXZdPGPF79erwtenK3pa/bEJiiXLW9nxQDE1vPTE3viFtci8SFZFwaKljkbclXJKsGuc/LjZ82u0FcIr6612luUmO8pkvUEVFFdq2mr94R8helkb/jklQfGoWbmlWrEnC3akV+WUPWCEZ4lW/M9PV8iluLxp7A1t7Ttg9TGBUIIHzHPTF3HwigIWbDX25SV0Z8Lgdh5fHK6JH8FrxU7CpL2u4RkPQH9a3K67vx4ua56a6GrcWQFu1iI4nttBWPnPGfiit1asi2/7QND5KVbzomuoLRKNe2t2hKmVbsKm61wCISrujY6PevRGDo3f1Ou/v31eu0qKHO87URS67O6fNg8/WbEIr0QZjnLK4bNV8qW+K9XT7KegOoqIDhxizVWY9CLK2pUEmHt65yiCn25Kvq9Kl5c5Kctw2dv1jlDZ+kTl8bU3z42LaoXaV6cKuHFmFpTU+vTE5PTdedHy5UdmDcwauG2mMYwOYRe0STtWItIvL0WvejDxdsdaafud5FXUqkh76XqP3O2cOe5gd0tlIv+bn2Odub7H397Xnhz79btKdINIxc7EpubSNbhCWVVtRr03LfaHMHqdkzubFlxRbVe+maD9hRWxKzmb1O1YVTiQHDR6jWUpI+W7NCYlO2atmaPHvp8tSSpNg4z49ziSn25Kivii/9ElixziJw036EVNus0LCW7Ooxx2V7k1KeEz2d107tLmj3OomYk60kr0i/9699O0fZ9zt66K62q1d8+Welom5BKK739QbdiR2JOynUyz7XW6q9jlunHT83Q5JW7nWu4gUkN2p23MTcq54g2n8/qd2+n6G+frNB9nzX+LKF3+YA7PlquL1dlaUcEn+H8POG0rMJybcsLbY5MsiFZT0KTV+7W/zw1Q38alRrRZI25UfhC35pb4nib8LZbP0hzOwTPm7cpT99m7FVpVW19Sctk1Vrxxi25JfWrI89ct7fd53A6EfViXvu3T1bo128taLHXsqK6NuJk3i1cRCSWeBx2Gg0k60nonk9XqqyqVnM25Oq79TluhxN3EqvSs/tiWRvZax/71lqt3Llf6btbvw2e1cI4ztYka8ISjXem10YChTskoKK6Nuj/obC8WtNWNx8S89y0DP3tkxW68s35Kq/y3p251G35+suYpY61V1lTq4cmrNJtHyyrn68BeAnJepLLKqyIWgIT7IrYY999iDORTnqurPFO8jFvU54GD1+oK99coFQHK+agbdZaz5WBa7pORUtGBFarDMVrMzfqlCe+UU4rxQZa+gnUTaYsqqgJOmnfzR/d9W+nODqG/N352zRu2S7NWLdX/5i4Wqnb8nXLqFSNW7YzpOevDKMKWax/bm99t0nXjFjoSEUUJ94vTi3a5ItRlSqvIFlPIsFe2sn1kvevGgjvCufDPKeoIqwvkFGLMnXqkzPaPM7ns6qNwZfBze8fWLXy9rHODQfatDdxh5M5kexk7S/XL4fN15VvLlBOUfR7UoOF3PSy838/bPs18MZ3oSfrw2Ztirj0ZqR3Epu+P9u61J67MVeDhy/UyAZVP7bklmj8sp0qjtJn96QVB+ZrzNmQq+vfTtHsDbl6aMLqNquq7QtUdfGiDdnFennGRi3fsb9RRZQ9heVauXN/1C5WW2v31ZkbW7ybGux10dLr7++frdSPn56hL1bsam+IcYdkHUnlmanrdNqTM/TPL1quipKkowc85ZJX5mrIe80rAjT17NR1Ouv5Wbp9bFrI4xo/XrJDVW2scLh7f7kuenmOLnxpdlTG7N776Qr99MXvtKBJz6CTww1++59FnrqDEE3tSTgemrBa67OLtTarSP/8Ij0KUbXPHoZg6Ob3U7Vy5349Nz1DuwrKVF5Vq2tGLNKDE1brmanrYh5P5r7WJzx+sSI6E76dsD67qNlje4sqdMGLszV4+EJ9tnSntu8rdTxpf2jC6lb3/+PzNXpz1qZGj+0rrdITk0NbZ2Hiit0qqqjRfZ+taneM8YZkPY5szinRDe8s1iMT17TrFlB7EtFES17fW+CvG/3xkh0tjv1MtrsMXhXKLe53A7/Lb9buVZWDJQ0fHL9KO/LLtKug3NHebsm/nsCklVnamV+um0K4IGmvGp9V+u7mX9TxrqX35/3jw//CXtCgbF6klW88NpKm3TZkF+u9BduUU+ydC4Yd+WWasS5bheX+HvW6NUQSUayGZA2dnqHqQCndf0xcowtfmhPxBWvT2L9Kz271+G8z9uqVmRubPT6LOXRBkazHkb+OWaqUrfv0SeoOTVieuB9a4SgordLE5bvatQBUNFakixkPXUWVV9Vq4vJdWpsVm1rB0f5SS9l6YGznuj2Jl/AGE+mP1alJrSPmbNb5//5O45a2PF64aZgTl3u3ZzNeVNbU6jcjFuqZqeualbx0W7ivy2/Wtr8KUCwNbzL3IFYLEJa0UMrXrcXyYikeKxs1RLIeRzIbvNicXqAhXt0+Nk1/H7dKN7+fmjA9XPFm2KxN+vu4VfrN8EXaF8PKLtHC68hdL369QbsKyusXZnJDLOYreMmaXYUqCwzDWrg5ukuzF7NYlSRpYwLNK9lXWuV2CG16fVbznvx4QrKeRGK9ol97Ogoqa3xh9ZwuCVTQWLenSMUVfAm44b9zt0iSqmp9ej8Gy9PHqgcqUk6GyQVEbAWrgNJe8fGKbVlL80Eqa2r1/PQMF6KJjmh9pLRVkjVR7C+jaEO0kawnkbTtsV0pMliC0Vbi8XUb492CidYHblsTEpNVOL2PLR05c91eXfXWAucCioHswgo9MnG1/jt3i+fK/rVkc06J3p2/1ZXa0Q2reTgpFj/3Va0s/76nMLya917Xnp/n+wsy6xefSnSRvNxu+2CZc4EgqR3kdgBw1uac4rCObyu/dSMdmZ6erV+e+j0XzuxXUFqlVbv267wf9tHtH6Zp4ZY8PTv4VF078Fht2lscdytIOnkRU1xRra25pVqwOU/DZ2/WH885vt1t3eqhL7KPl+zQacf2ajTxsCUPTlhVPwSt/1E9YhFau9X6rK777yIVlFVr+po9mnjHeTE9/3PTM3Tasb006MTDY3pep1TX+tSpY/P+rD+Pdu516/3LvZbF4g5aIshq4SLZ7RuD32Y4M6Z/7sZcPTN1nS7sf4Qj7aF1JOsJ5oWv1rsdgmuc6HCr9Vn96o35yiqs0A8O76btgXkCD4xfpWsHHqs/jVqq3WGuJhmujXuL9dWabP36f76nE49oOSF0o7e/sqZWP3tlbqPJvHVDYEKxPd+7PXHBSnnWSduer6HT12tZg7tTX6xwdqiE0zLzSlUQuD29fEfoi7Y4adb6nLhN1itr/Ml60+QqI4kmHcfaoi3MxXJS0yGD4X5vNB0627C9ujUiNuckzth7LyNZj1NfrspSYXm1Hv/Vyep3VE+3w/GEz5ZGPqM9v8FEme0tzB6PdqLu81n9ZvhClVbV6uPU7Vryz59H9Xzh+GL57nZV3akTz6UEf/ufFLdDiDq3e/xC5bXRR5H83LzwI/fKHJBan9WNIxuXM339200Jt7JvRbWvxc/RVTv363+OOzSq5y4Nc97aG01qobvBqfd7qGtxeBVj1j0ia3+5fv3mAl0zYmHIFTXmbczVn0Ytjei8bb0P4unlXergojLtFenPq7Sqpv7/sbfIW5VVyjzw83VDrFfJ25lfprGLtzf6Qk+PUVnMROaRnDT+RPhzqwyxN7elRbxilajHOpH71+Tmdc2vHr7QM3cWfD6rRZvz9E6U5p0gfPSse8TVwxfWfzk/MWWt3rrxjJCeF+2e3kjw5YhoiPXrKpar5Pl8Vn94d4l25Jdp6uosfXrbOdqcU6yPl7TjrlGYPyev9VgHw+eK86L5q//9O4vbPsjDrLWN7rg6IdiiQbeO8cY8nivemK/12eHNf0N0Odazbow51hjzvjEmyxhTaYzJNMa8bow5LMTnX2SMsSH8Oc6pmL2kYS/a1NV7XIwkeiav3K0LXpyt17+N73qn7UWOgdZYWWUVlmtHvn/41eKt/l7Fxya1c3XBOEm+wxUvFxUNcYERv+78eIXOeGZm0P1ODiMqb2FV7ViblbGXRN2DHOlZN8acJGmRpCMlTZa0XtJZku6RdLkx5jxrbVsrLWRKeirIvlMlXSMp3Vrb8rJ2SeynL36nZwefqgv7HxG1L7JdBZGv/lVXRaUuGUk27f3VFFVUq0dnboIluopqn3bmN79TVrc0OCLzXUaOjj20m3p16xTS8anb9un04w5Tl05JPlo0gV9+tdZqW16pbCv/ybwEWOgtHH/xSO8+GnMqAxghf6J+t7X2zboHjTGvSrpP0nOSbm+tAWttpqQnW9pnjPkk8NeRDsTqOeURjgXemV+um99PVeYLv2rX89uqs5tXUqmfvTw35PaenLJWpZU1uuTkI9sVT529RRX691frdVSvg/XgpT9Shw6J2z2Vmecvh/jTfn0aPf7Vmj2657OV6tu7m0uROcPJ35y10qNtVG+JVzeMbDxkwM1a7gVh3vr3eo/3KzM36ouVuzXr7xeGdPyfRy/T4d0769s2jvf6/7st1tqkveu3v6xaF788x+0wYiYe7/CEOuehLfH4f28o4mQ90Kt+qfw948Ob7H5C0m2Shhhj7rfWhl27zRjTR9JvJJVL+iCyaL3HWqvfjFgYs/Nt3xfer6Cy1qc3Zm1SVW3ob5jRizIlSYu2RLZs9cOfr9acDbmSpBP7dNd1Z7o7Aipte3QmO9XU+nT92ynKKa7UmT9oPGrs/z5aLqn18ljB6kG3JRrlHyurffo0NfKqPK35Oj1bKVujuyS6V7R7CIwDnpueoaMO6eJIW7UeuTuwNbdUG/aGfot/X2mVPl8e2QTjWp+N76Xl4zzJiSdhrDPnCrc6D5L1bnxDTtzfuziwnWGtbfTtb60tlrRQUjdJZ7ez/ZsldZE03lrrTrHgKJq7MTem48Oaloxq63O4qsaninaOo4t08mtdoi5JX6zYHVFbTohW+b6MPcXKCfxeloW5yuzs9Tka+MxMXf92Sv2Koum7C/WLV+fqr2OWqrqVi6zRi5xf2OSDlO36x8To9novi9JFU7jaeu84UWHio/ZMLHXIhDTnquC8u8A7i+j4mr4ljFp9n4TTUdGS9qzInF9a1ern7vDZmyO+IxuvfF7PaD0kUa6zXvpmg9shuM6JYTA/CmyDzRrcJH/Pe39Js9rR/q2B7duhPsEYkxZk14B2nD+qHpyw2u0QEMduGe0v3Zm6LV+fLd2pGwf11U3vLdH+smptyinRmEWZ+vX/HNPic5dvd/7aN9LEJhT+JJgvbK8Jdpu5pYv26lpf/Uqwbquq8encF75r9/O/Ss9W1v5yHXNo1xb33/nx8rDam78pV38ZvUzdunQMesxL32yovzh3QyTrLUTqnfmUE4wHVTU+LcvM1xk/CKnGCNrgRM96r8A2WCHgusfDrvZvjLlQ/ouBdGvtonbE5inWWqVtL2g0FCXexztGQyxvtbk5JthpmYHX1f7AqpWStCyzIGF6VxAmB37xTrw9WhpuNXbx9sgbbiB9d2R16CNNPu/7bGVEz29oyHupqqr1NXoft+TVma1X1WrtbkE8a88q3Zv2FuvDlEzHSzDGm5dnxK6H+q6Pl+vGd5foxpHxXbrTK7xeYuK2wPadcJ5krR3Y0uOBHvfQCpg76Pr/pig9q7B+URljpLkPXKy+hwefNLhiR4FO7xv+FWnipJ7RZ2SC1ruNRH5plUora3RcnE8KdVJxmCvnIXLh5uqx/OyIZBx4SxcQv39nsdKfuiyCiCKzpJ2L90Rz9VBfiFdaxhhPfG9Eq9+korpW1/xnkYorajTPI3dzoqm1V9TYxbEbVjdj3V5J0vId3hi9HO+dVk70rNd1afQKsr/u8bB+Y8aY3pJ+K//E0g/bF5o3VNTUNlr90VrpyS/XtvqcNRH2FCWaSCerBuP0Cnk7C8p09tBZuuCl2ZqzIcfRtgEveNeBYQjpu4sciOSAkiheDCbQzbegWhsHHmqSM2dDjipravXctHXOBOWQJdvyVVzhf33MDCSQQLxxIlmvu6/SP8j+foFtuCvh1E0sHRfvE0sPaqHkYFlV/PQ0euXLqrrWp/TdhZq0Yne7J71G29LMAlXV+GSt9KdRSxvti/cr+005LJQB6dlpGZ59/+GA1ipINbSroEy/c2CV0T+NWqpXZ27UyPnemUwcC7sLvLuKOBKHE8n67MD2UmNMo/aMMT0lnSepTFK4nwZ1E0vDGgLjRSt3Nr/WcKJShBM8koeHJLuwQoOHL9S9n63U8NmbI27v7XlbtC0v7GqicaWoovVxr+H4JNUj65F5463TptYWWgmrnXZeLUfzvV1Z7d54aKd+rl6wvyx6Y6hDHUf/+rebHDvn23Pbf9clHutgV1TX6v2FyXNx4rNWe4sq3A4jKUWcrFtrt0iaIel4SXc22f2UpO6SPmxYY90YM8AYE7QyizHmp5JOVoJMLI3lpP1oTJgc72AJt0j8d+4W1QR+mG9+F36yPnV1VqN/v/7tJs3dmBvkaOe5kWIs2rIvakOI3BKH3+lxId5/rtvySh0tNxkLz0/PiFrbWftJqqIt1sNqHp6wWhe9NFsL2hh7n7W/XHd9vFxDHX59/fY/KRr0/CxHhsIhPE6to3yHpBxJbxhjJhljhhpjvpN/9dKNkh5tcnxG4E8w7ZpYGk8irV4QTLgJYTx9QUea7N718QpH4og39zpYqQIHxKonsKVJiP/8Yo2WtLEwVFG5c3dVWlJZU6uv07O1s40FS2L1GXPNiIV6Z158JRFLM8NbVyGRPTXFW2PdQxHqJF6nfLZspzL3lemm95a0etz941Zp6uo9yiqMzgXbs9Oid5EZLV7pdGwvR5L1QO/6mZJGSxok6X5JJ0kaJulsa23IXXvGmMMkXasEmFjamuLKGl3yyhzllbhXrxbJbWdBaKvCPTZpjXK49ekpHy/Z0eY442j22krSi19v0O1j03TFsPkxm4NjbfA5NAVtlDpMNk5Nuo1mxZqGPlsWnWF28dQh5ZRkWeE5mThWutFau1PSLSEeG/T9Y60tkNTy6hIJZktuYo+XdppXJro6zY0xuEOnZ2htVmgVOcYu3uGpW+oJ+jIIKi3MVW3rRHv43XuBVUmLK2v0edounXhEj2bHvDNvq7aEONExFLv3l+u5KF+EAPHi09QdGj4n8vlb8D6v11lPWu3pDbDWJu0S1Ah9vsK8jbl6O8zhAt+tpwxluLwyiTxULb16Mva0fEE3dknjRY1auzCY5eBrp9ZnKb8XY4m0cFyi+cfENW6HgBghWfeo9nw8XvXWwrDrsxdVVHuupzJWt11jYeS8rdqwt1j3XNKv7YPDNG5p+24b//H9VIcjia3EeXW4Z1dBmdJ3F+mInp312/+kqG/vburYQonZ2RtanoD90jfNV0IMltjHu6mr97gdAiLgte83oD1I1hNIexZSeumbDbrp7B9EIRrnxWMOX3fLfktuiTp1bHmKSHt7YB/6fHW740LyKquq0S+Hza9fKEaSdrQxSbQtPmvjZtJZuJ8jiXoRkiy+jeKdGDc7loLdRW/vxYm1NqE6yhINyXqS8+IdzlBvu8bT7dkVO/brrBN6ux1GQuD7pH2qa33q1LGDPl++u1Gi7oQKF+uuI7riPYGLZhGHmlr3XvenPPmNo+395Llvdd4P+zjaJpzjVOlGREGtz2r7Piah1mmam78yI9xFcd0V3195iHcfpvjHmde6mGB4QW0MF76oqknun3Uiq6yp1d/HrXLt/E6/jvNKqjR5ZVbbB8IVJOseZa10wzuLdeFLcxxf2CBRvBXCKqZnPz9LQ95bolKHypgBddq6+PLaSpsz1+2Nq7tR0fJRk8mx0fRJ6o6YnQux5ZkVnZEUSNY9an12sVIz8yUp7ModOCC7qELzN+Xp9W/d74UnTUoui7fmux1CIylb9+nS1+apIgq9vfE0UmLi8t1RabelC6EnpqyNyrkQunh6bQLBkKzHwBWnHh32cyqqKcHYVCTjA+e3sTwz4LQvV3nvlvKmnBL9d+4Wt8NISAs3H1iIxlqrr9OzXYwGQCIhWY+Bow452O0Q4s7LLZSGi/flgvNLq9wOAQ7aF6e/z/1RWOmzvQs3JZLHJh2oeb14a75uH5vmYjTOoWMacB/VYGKg/1E93Q4hrqRuy0/I2sabHVzJsSXJMhzZK4sNcbfmACdXKU0Ez0xd53YIABIIPesx4GZ5p3iUU+x8qa312cWOt+kUr01EhHNyiircDgGIyPPTM3TFsPlK2eIf5rO/LL7uKHnl4h6IBMl6DNS0o8TSFyuiMwkKQOyc9fwst0MAIrKvtErr9hTphpGLJUlDp693OSIg+ZCsx8C5J7HQAOCUciZfe86ugnK3Q0CMbM1jyBMQayTrMXBIV6YGAEhcVQz1AzyBtRQSE8l6kqHmbOLidwsgmtK2e2vtADT381fnuR0CooBkPQY6d/T2j3lvIZPg3LKvpFLDQ1iJFQDcdsM7S9wOIXwudGIMnZ6hfSXOF0pA8mJ8Rgwc3qNLxG1E89bW45PTo9Y2WvfIxDWasW6vY+1VMxwBaBV3oNqP4U6heXveVu0prJAxyVNSF9Hl7S5f1HsyistWe21Z9GTiZKIuSRPifOEoIBGQn2GKB1cwRvwiWY8TY1K2ux0CHBaNFU0fmbim7YOAJFZRHf3e4USur780M75Wq3XzRgq96nAKyXqSqarh08MrnnD4bglfDIB7MveVafyyndqWV6p9UbgQB5C8GLMeIz8/+Sh9m+HskIf2qFvYAu770uHbpOTqgLsenLBavbt3djsMAAmGnvUYueeSfm6HgARXWF7tdghA0ovG8DYAyY1kPUaOOiTyijAAAABILiTrMXLkIQe7HQIAAEll3sZct0MAIkayDgAAElJRRY3bIQARI1mPoWvO+L7bIQAAACCOkKzH0PLt8VWfFgAAAO4iWY+hnQXlboeABEaddQAAEg/Jegwde1hXt0MAAABAHCFZj6Fbzj3e7RCQwCzLIgEAkHBI1mOoa+eObocAAACAOEKyDgAAAHgUyToAAADgUSTrAAAAgEeRrAMJYktOidshAAAAh5Gsx1CPLp3cDgEJbNWuQrdDAADAk6prfW6H0G4k6zF02f87Skcd0sXtMAAAAJLKuGU73Q6h3UjWY+igjh0076GL3Q4DAAAgqTz6RbrbIbQbyXqMdTmoo64beKzbYQAAACAOOJasG2OONca8b4zJMsZUGmMyjTGvG2MOa0dbZxhjPjbG7Aq0tdcYM9cY80en4nVTNxZHAgAAQAgOcqIRY8xJkhZJOlLSZEnrJZ0l6R5JlxtjzrPW7guxrbskDZNUIGmapN2Seks6RdIVkj5wImYAAADA6xxJ1iWNkD9Rv9ta+2bdg8aYVyXdJ+k5Sbe31Ygx5lJJb0iaKelaa21xk/0JUU7lZycfpTEp290OAwAAAB4X8TCYQK/6pZIyJQ1vsvsJSaWShhhjuofQ3EuSyiXd2DRRlyRrbXVk0XrDBf36uB0CAAAA4oATPet15U1mWGsbFbG01hYbYxbKn8yfLWlWsEaMMadIOk3SJEn5xpiLJQ2UZCWtlDS7afvxyhjjdggAAACIA04k6z8KbDcG2b9J/mS9v1pJ1iX9JLDNkTRH0gVN9q8xxlxjrd3czjgBAACAuOJEst4rsA22fGLd44e20c6Rge1f5J9U+itJCyQdJelfkm6SNM0Yc6q1tqq1howxaUF2DWgjBgAAAMAzvFRnvS6WjpJ+b62dbq0tstZukvRHScvk753/rVsBOumiHx3hdggAAADwOCd61ut6znsF2V/3+P422qnbn22tTWm4w1prjTGTJZ0pf0nIT1pryFo7sKXHAz3uZ7QRR0wcf3h3SbluhwEAAAAPc6JnfUNg2z/I/n6BbbAx7U3bCZbUFwS2XUOMy9N6HuxU1UwAAAAkKieS9dmB7aXGmEbtGWN6SjpPUpmkxW20s1j+Mo/HBynzeEpguy2CWD3jB4eHUskSAAAAySziZN1au0XSDEnHS7qzye6nJHWX9KG1trTuQWPMAGNMo8me1toySe9JOljSs6ZBfUNjzKmS/iSpRtKESGMGAAAA4oFTYzHukLRI0hvGmEskZUgaJH8N9o2SHm1yfEZg27Tg+OPyl2y8V9I5gRrtR0m6Rv4k/t7AxQEAAACQ8BypBhNIoM+UNFr+JP1+SSdJGibpbGvtvhDbKZL0U0nPS+ot6S5JV8pfwvEya+0wJ+L1gl5dO7kdAgAAADzOsVmO1tqdkm4J8digS3haa0vk74lv2hufUC4ZcGTbBwEAACCpeanOelLp0MHozotPcjsMAAAAeBjJuosO7drZ7RAAAADgYSTrLrp24LFuhwAAAAAPI1l30UEdgw7dBwAAAEjW3eSzbkcAAAAALyNZdxPJOgAAAFpBsg4AAAB4FMm6iyxd6wAAAGgFybqLDu7U0e0QAAAA4GEk6y46uFNH/eq077kdBgAAADyKZN1lfxjU1+0QAAAA4FEk6wAAAIBHkawDAAAAHkWyDgAAAHgUyToAAADgUSTrLjv20G5uhwAAAACPIll3Wd/DSdYBAADQMpJ1Dxh6zaluhwAAAAAPIln3gI4djNshAAAAwMIeoi0AACAASURBVINI1gEAAACPIln3gPN/2MftEAAAAOBBJOse0KdHF7dDAAAAgAeRrHuAYcg6AAAAWkCyDgAAAHgUyToAAADgUSTrAAAAgEeRrHsAQ9YBAADQEpJ1AAAAwKNI1gEAAACPIlkHAAAAPIpk3QMMhdYBAADQApJ1AAAAwKNI1gEAAACPIlkHAAAAPIpk3QMYsQ4AAICWkKwDAAAAHkWyDgAAAHgUyToAAADgUSTrHkCZdQAAALSEZB0AAADwKMeSdWPMscaY940xWcaYSmNMpjHmdWPMYWG0MccYY1v5c7BT8QIAAABed5ATjRhjTpK0SNKRkiZLWi/pLEn3SLrcGHOetXZfGE0+FeTxmogCBQAAAOKII8m6pBHyJ+p3W2vfrHvQGPOqpPskPSfp9lAbs9Y+6VBcccEYo4cvH6B/f73e7VAAAADgIREPgwn0ql8qKVPS8Ca7n5BUKmmIMaZ7pOdKZP930Uk664TebocBAAAAD3GiZ/3iwHaGtdbXcIe1ttgYs1D+ZP5sSbNCadAY8ztJJ0iqkpQh6TtrbaUDsXoaRWEAAADQkBPJ+o8C241B9m+SP1nvrxCTdUmfNvl3jjHmTmvthFCebIxJC7JrQIjnBwAAAFznRDWYXoFtYZD9dY8fGkJbkyX9WtKxkrrKn1wPDTz3M2PM5RHECQAAAMQVpyaYOsJa+1qThzZI+qcxJkvSm/In7l+H0M7Alh4P9LifEWmc0WLdDgAAAACe4kTPel3Pea8g++se3x/BOd6Vv2zjj40xPSNoBwAAAIgbTiTrGwLb/kH29wtsg41pb5O1tkJSceCfVJUBAABAUnAiWZ8d2F5qjGnUXqAX/DxJZZIWt/cExpgfSTpM/oQ9r73tAAAAAPEk4mTdWrtF0gxJx0u6s8nup+TvCf/QWlta96AxZoAxplFlFmPMCcaYZoXGjTFHSBoV+Oen1lpWMQUAAEBScGqC6R2SFkl6wxhzify10QfJX4N9o6RHmxyfEdg2LC1+oaT/GmMWSNoqKV9SX0lXyD/ufZmkhxyKFwAAAPA8R5J1a+0WY8yZkp6WdLn8CfYeScMkPWWtLQihmTT566sPlHS6pEPkH/ayRtI4SW9ba6uciBcAAACIB46VbrTW7pR0S4jHNlus01q7RtKfnIoHAAAAiHdOTDCFUyi0DgAAgAZI1gEAAACPIlkHAAAAPIpkHQAAAPAoknUAAADAo0jWAQAAAI8iWQcAAAA8imQdAAAA8CiSdQAAAMCjSNY9xLIqEgAAABogWQcAAAA8imQdAAAA8CiSdQAAAMCjSNY95OBOHd0OAQAAAB5Csu4hz1x9ioxxOwoAAAB4Bcm6hxzfp7tm3neh22EAAADAI0jWPeaHR/ZwOwQAAAB4BMk6AAAA4FEk6wAAAIBHkawDAAAAHkWyDgAAAHgUyToAAADgUSTrHnTsYV3dDgEAAAAeQLLuQR1YGQkAAAAiWfekv5x/gtshAAAAwANI1j3oxkF93Q4BAAAAHkCy7kGdOvJrAQAAAMk6AAAA4Fkk6wAAAIBHkawDAAAAHkWyDgAAAHgUyToAAADgUSTrHtXvyB5uhwAAAACXkax71Hs3/8TtEAAAAOAyknWP6nt4N53y/UPcDgMAAAAuIln3sEMO7uR2CAAAAHARybqHWet2BAAAAHATyToAAADgUSTrAAAAgEeRrHuYFeNgAAAAkpljybox5lhjzPvGmCxjTKUxJtMY87ox5rAI2rzAGFNrjLHGmGedihUAAACIBwc50Ygx5iRJiyQdKWmypPWSzpJ0j6TLjTHnWWv3hdlmT0ljJJVJYoUgAAAAJB2netZHyJ+o322tHWyt/Ye19meSXpP0I0nPtaPNYZJ6SRrqUIwAAABAXIk4WQ/0ql8qKVPS8Ca7n5BUKmmIMaZ7GG1eLekWSXdLyoo0xnh17cDj3A4BAAAALnKiZ/3iwHaGtdbXcIe1tljSQkndJJ0dSmPGmCMljZQ0yVo71oH44tY1p3/f7RAAAADgIifGrP8osN0YZP8m+Xve+0uaFUJ7I+W/iLi9vQEZY9KC7BrQ3jbd0KGDcTsEAAAAuMiJZL1XYFsYZH/d44e21ZAx5s+SrpL0O2vtXgdiAwAAAOKWI9VgnGCMOV7S65LGW2vHRdKWtXZgkHOkSTojkrYBAACAWHFizHpdz3mvIPvrHt/fRjvvSyqXdIcDMQEAAABxz4lkfUNg2z/I/n6BbbAx7XXOkL/8Y25gESRrjLGSRgX2Pxp4bFJk4QIAAADxwYlhMLMD20uNMR0aVoQJLGx0nvwLGy1uo50P5K8a01Q/SRdIWikpTdKKiCMGAAAA4kDEybq1dosxZob8FV/ulPRmg91PSeou6W1rbWndg8aYAYHnrm/Qzt0ttW+M+ZP8yfo0a+1jkcYLAAAAxAunJpjeIWmRpDeMMZdIypA0SP4a7BslPdrk+IzAltqEbfjhkT20OafE7TAAAADgAifGrMtau0XSmZJGy5+k3y/pJEnDJJ1trd3nxHkAAACAZOJY6UZr7U5Jt4R4bMg96tba0fJfBCQla63bIQAAAMAljvSsAwAAAHAeybrH3X7hSW6HAAAAAJeQrHvc2Sce7nYIAAAAcAnJuscxZB0AACB5kawDAAAAHkWy7nFWdK0DAAAkK5J1AAAAwKNI1j2OMesAAADJi2QdAAAA8CiSdQAAAMCjSNY9jlEwAAAAyYtkHQAAAPAoknWPs8wwBQAASFok6wAAAPj/7d13nBT1/T/w13v36l7vxzWuwTUOOO644+7g4ACpIggIolKlCTaixhpLjD819mBNgpqvscUYNcVoYo8aS0zR+LX3fG2xCyoWPr8/dg6OvS2zuzM7M7uv5+Oxj4XZKZ+b2Zl9z2c+n/eHbIrBus351qtnpSVZUg4iIiIiij0G6w5z5SHtVheBiIiIiGKEwbrN5XtS9vp/T10BzlnYalFpiIiIiCiWGKzbXF5GCk6e04SRJZnYuqwNIoKl4ytx1XLWsBMRERHFOzaAdoB1fbVY11e7+/8igq6afAtLRERERESxwJp1hxKI1UUgIiIiIpMxWHcoxbFNiYiIiOIeg3UiIiIiIptisO5QHNiUiIiIKP4xWCciIiIisikG60RERERENsVg3aFyPcmoLvBYXQwiIiIiMhGDdYcSEVx3aBey0pgqn4iIiCheMVh3sMp8D545fSYWjauwuihEREREZAIG63EgM9Ud8LMb1nbFsCREREREZCQG63Gup77Q6iIQERERUYQYrBMRERER2RSD9TjQOCzb6iIQERERkQkYrMeBJR2V6BtZhLRkHk4iIiIiXznpyVYXIWLM+xcH3C7B/6zphFIKv3v6HRx54z+sLhIRERGRbfTWF1hdhIixKjaOiEjU66gtyjCgJERERERkBAbrtJfO6nyri0BEREREGgbrREREREQ2xWCd9mJASxoiIiIiMgiDddqLUlaXgIiIiIgGGBasi0iFiFwtIm+LyE4ReV1ELhaRvDDWcZyI3Kktu11EPhORZ0TkQhGpMKqsREREREROYEjqRhGpA/AogGIAdwB4HkAngKMAzBKRXqXUhzpWtQHAdgAPAngPQDKANgBbABwqIlOUUsxLaCI2gyEiIiKyD6PyrF8Ob6B+pFJq68BEEbkQ3kD7LAAbdaxnlFLqK9+JIrIOwE+19cwxpMRxyumxdktZNp59+zOri0FERERkC1E3g9Fq1WcAeB3AZT4fnwZgB4DlIhIygbe/QF3zK+19RITFJIe45MA2q4tAREREZBtGtFnv197/pJTaNfgDpdTnAB4B4AEwIYptzNPen45iHeQA5bnpVheBiIiIyDaMaAbToL2/GODzl+CteR8J4F49KxSRtQAqAGQCaAUwHcAbAE7QufxTAT5q1LO8k6Ulu60uQlTSU5xdfiIiIrIfJ2e7MyJYz9HePw3w+cD03DDWuRZA16D/PwngIKXUy2GWLeFMbSxGZX463vroS2zoqw05f2d1Pp54/aMYlIyIiIiIwmXLPOtKqQlKKQFQCG+tPAA8JSIzdS7f7u8Fb5aauOZ2Ce4+ug93bO7FCbNDP0i4eUN4rZNGlmRGWrSQhhd4TFt3IAeOr4z5NomIiCi2nFyzbkSwPlBznhPg84Hpn4S7YqXUh0qpP8MbsH8J4DoRYaPmEDwpSRhTmQvRkYdRRNA+fE8q/NmjhgWct60qF1ct7zCkjP5sWznetHUHcs6i0THfJgGb++usLgIRESUQBedG60YE6y9o7yMDfD6QwSVQm/aQlFKfAPgrgCIALZGuh/y75MCxWNZZhTMXjMK44f7HsJrTWorbNvWipjBkUp+I7N9Wjvpib639OQtbTdkG2YfbZcuHekRERLZjxC/m/dr7DBHZa30ikgWgF8AXAB6Lcjvl2vu3Ua4n4YRqulKR58HZC1uxfMLwGJVoKDXo+dSBnVWWlYOIiIjITqIO1pVSrwD4E4BqAJt9Pj4DQAaA65RSOwYmikijiOzVoFpEqkSkxN82RGQDgPEA3gLwTLRlTjRXHNKOkSWZ6Bieh0XjKiJax35jygwuVXC3berBsk62J49bTm48SEREjuPknx2jRjDdBOBRAD8RkWkAnoM3m0s/vM1fTvaZ/zntfXCj6nEAbhGRvwJ4GcB7AArgzc/eCmA7gOVKqe8MKnPCqCvKxN1H90FEcOod/w46b5Jr73bui9srUJXvwcyWUjOLOERbVR7aqvJw4xNvxXS7RESUmH6xphMrr37C6mIkvKZh2XjuHeNHMndwrG5MNhitdr0DwLXwBunHAKgDcAmACUqpD3Ws5u/a/KkA5gI4FsAyePfvBQCalVIPGlHeRDTQ2XRXiFvLtGQ3NvTVIiXJhaOnj8D5B4zBkdNG6OqsqldtYQay0oy6TyQncvJFk4gSx8K28tAzkaFqCmOfGc7uDIuYlFJvAVitc94hkZ9S6k14A3Qy0Xe7Qs9z4pwmHDuzAcluczoB3r2lD+PPuseUdZMzhLppJDLT1mVtOOLGf1hdDHKATFYsxZxZPw9O/tlhSoYEo3R+W80K1M1et6+eugIku417KkDOlhLD7x7Z17wY98Eh53JygEe+nHsw+cuVYIyo0bxmdezzoUfqnIWB86jPCrMdvtMDvZ8sa7O6CLtNqC2wZLt3HjXRku0SEQ02vtp/mmS7mj+WN7hWcnb0QWHbZcCNZX9DcdTrqDUpX7uvqgCjos5sKcHFB46NSRnsYt7owANexZonxZpHy/XFWWgoybJk2wPW9NZYun0ist4tG3uwT7PfBHhkEic/JWGwnmCsaCu8uH1ousgLl1gbKE9pKEZastvSMsSaiKAsJy3q9dy4boIBpQE6q/MBAKlJrpjm+Dewr3RQw3z29RFT63H5wePw/VkNsSkAEdmak5poxjp0WNVTHfTzjJTwf78dHKszWE80sT7h9mkuQU/d0CYP1T416+Fmm0lN4lfXKkYFu1sPasNJcxpx++ZeHD+7MfQCBonFOVCZn45HT5jqM82DOa3DkJbsjvm4BUQUmr9LmyfVvEod8btFmtM6DHmelKDzXHrwuBiVxh4Y8SSYWNes/2xFhynrvePwXt3zOvnRlx0Z8/OiUJKdhvV9dWgalo3M1CQcNzN+apz/cOSkoDegxVmppm17TGWuaesmimf+TtneukITNxj4o+wEzkKz7+hhUCHqwUeX54S9Xr0JNuyIwXqCMaLNerhGRXBShdJYmm34OkMZU2n832FnuZ7kmD7B0LOtU+Y24ZpV43HGfi0YVR7774AeWalJyE5LDjqPWU1xztivBXds1n8jG88mjyyyuggR8R2YjqwVq2ZzQ7ebuN8DPX97QWYqDu6qCmu93X6e8jsFg/UEs8uCaH1kSRZOmtOI3voC3HpYd8y3b4SS7FRccEBidUitL8rEnUdNitn2lnVWISs1eG3Siu5q9DcWY2VPNSaNcGYwBgDr++pMaa+6yE//kETUUpaN8xYHzgRF8amuKDaJC4zipHBcIfwMamY7a/9WHDalTte8wws8WO3gzv0M1hPMhEF3lqXZkXc2PGJqfVjzr++rw/VrJ6B9eH7E27TSw8dPDZhZJl4UZAxtI1iemx6z7WekJuGeYyYHnSclTvoqFGWl4rZNxteAZ4a42YknoWrVirPTMLOF2TbIPzvk2i+J4jfYCpfFsJ243vb8elMqX3Fwe0zHeDGac0tOEVk2vhL7jSnDmMpcXLsm8nzpR08fiVYTmreE49bDejC1sRhn7T/K9G0NnOROb1cd7PHiA8dNGTLNX8YclwGP6QM1HXTaj1c0zGgelkgaSkOn4Ix1B77uMMcP6KwZWnlRnhe7G+RI9DfY94lWoGBsQu3Q/Vyts/Il3GbOnhQ37jtmMi5cMibkvEdNHxFku+Y+BR9dEf71x+0SQ/rErOwejtoAT0EO7/dWBBrdCihUG3i7Y7CeYJLcLvxkWRvu2NwbVbtvt0swaYSJHW90aB+eh6tXjcey8eG1WwOAaY2R5Yo/dGINTprTOCQtXzzICtHOeoArgdtSRqMoM/xOpZF+TweLx++qXS0dXxnW/O3Dhw6Mk+J24dbDeowqkuGsrqTZGmRwNzuk4z24qwq1RZlYOC50k7RQfVvsKDc9+jKfMX8UfrG6029AnpnAHWuDYbBOEXPqfeovD+1CcYQ1uGnJbqzvq8MhJuUFP2VukynrNVJbiJoVf3nEt600JyvQYP5ShFrt7IWtSHIJumryMSWCGknfFKeRWNVTjfuPnRL1emioSI6pHv6CePKKpPlKdYGz2rKHY0lHhSN+N3xV5nvw5y2TcXmMmtY4PU0mg3VynJElmVEtP9HiJwLBpCW7saQjcI2MnkerRvFX61FfnBm0Gcz+beWYN3roj6kRQWe0rMgOsqyzCv84dR/ctH6CpdkdagozMNaAx9ejK3KwsK3cgBINNb0pvPblsczCdtzMBlTkpeNon2YLVtcyWyGWlTQPH98f1vyBTrETZjfC97Ll4Cx+ezm8fwRWdFeHvVy4V6OjpgVushOp+uLMIZUsA23Qm4fZM9uXVRisk2HcMUg5tqGvFj9fEV5b+1PnNe/+txNqIIblBG6zqufRqpnyPMEfgaYmufz+YNb6BOux/p1sq8rFOYtaY7xVr6y05IgDdTsFFGfOb8FvD58YtK39JQdGkzHJRn+sj/3byvHw8VNx9PSRQecLN3++nY6vHRnVwT3XzwA7CmpIfyd/ta9mHKKzFxp3Laoq8PjteB+s0idcN6zrQn1xdJVkgfju8+Js7zk0rakYSzoqUFeUgZvW7z1q9hoHZ3WJFIN1MozZ+Z1dApw4pynsrCwHjq/CKXObcNKcRizvNqb5SltVYg48oye48DdPLGqVg7X/vG1Tb9CbIKv8bEUHSrLNGyAJMCbYcAmwXEft3fyx5tS6R2ppZ3htyKPVXVeAKQ1FSHG7Ig7I9PQJiWWWJl/htsuPlpljPSzp2PtvMeIyta+fJ4u+lnWG7me1v44nWBsm1/qd3lqeM6T9/jk+38dwrgs9OgeGCtRpNKgA+1xE8OPFY3DvMVMwwafjdnpK4oWuifcXk2lGlefEpHY9XClJLqydVIv1fXVITTKmA1JPXWHAC2Ui85fn26y25Gk+x/LUec2m5C430z7NJXjsxGlWFyOke4+ZYvo2jKxlHljXlJFFOHXf5r0+WzvRvFo5EcG1qzvxr9Nm6ArI/Dn/gNBN3azMGFOcFbsOyyKCI/00vxi4ESqLsvO00an8DmivMGwE4WNnNmD2KP95zY+YWo/1fbU4Yqr+pikLDGq+Fuw03bZy/JDKh4HsLhQdBusUsVg8wh3cjnWfZn1tWgdqYo7ZJ/gj62idOLsJN66bgHSdGQiuWRV5qsxo5fvJoW6kNb01OHthK8ZXD02Rdp6O4EMP38e6qydWw5Pi3ffHzhiJstx0PHz8VPzhyImGbC9S4Z4WThipsMagPgeHTqyJaF2NOtI0+iMiWOMTnPtLlxipnACZMdJT9F0TfA/9mt4atGop9Q6McQ22mUaWZOK6QzsjWtZfzfqyzio8csJU3O+TbtbKM6k8N33ItS6a8yYrLRlXHNKOwsyh1+5jZjTgpDlNQcdVsGLMhZrCDDx8/FS8fNZsXLN6PM5cMAqb+vUNWhTK4HrAsZWJ1wGbwTpZZsygPK8zA4yM9v/2H4W2qlyMq8rFmQv05VO/53uT8Ys1ndgUgzv67roCPH7yNF0/rP0GpOGzq1PnNQesSfT3yD6SG72zF+49ImV2WjIeOHYKbljXhU1TvMe6JDsNLWXRdfrTe/PlNHa4J/jBvs0BM9ME+0r8Yk1nWDecZv6tN6ztwsyWElx5SDtSDf6ujK/eE4T01AduemDEn5eTnozbN/fufvJVV5SBLh03MpHs21s29Bg+4nB5brphT0qDiSbf+ZWHtIfs5xPKz1ZElkkrO8oUi+cfMAbTm0rCHnU82e1CktuF/oZiLJ8wHJ6U4DcNvt+nQLv71sN60Fqeg4O7qjC9KX5/SwNhQkuyzKUHjcM5dz2PusKMgCMNFmenhRzp0fdkr8hLR2W+caONhvpxyk5LxklzvW3ph+dnYPMNf494W1b3NyvNTsO7n30FAH5Hm7Uy4PPXxKo4Oy3iNJyBtJRl429vfBzx8t8z+InO6fOacfrv/jfoPO3D83DC7Mag89ggVo9YSXYaDmivwFUPvWp1UdBTX7g7kL7usTcsLk3knjh5GlKT3Lh+bRc+2P41irJScf7dL+Dx1z4Kulyy24VZLaW469l3Y1LOJBs2rdSroTQLfz1xGjrPugefffVtROtoq7KmFnlxewUW+2nWaJW2qjz87oihT031Nr3loEhEEarM9+Cyg8bhezMaLG0KoHe44mCy05KxaUo95o4e5vfzdZP0t5MNtCsCtf3TM6R6S5m+NFhXrxqPmsIMdFbnm5KqSw+zc7J7Us2tjdPbXEsPBYVVvTW4++g+XBEkH/Gth/X4bYLkJOHWYJo5wmNulLWhdrewrXx3rbSIoEjLYqM3oLn84HFDrml6RwQN1wEdlcjSmnSEuo5G+1QtGoEyIaUlu/1mawlHqBvxSMRysLRrVu9pAnpQV2R9ORIdg3VKeH89cWrQz6O5jZhQm4/zFo/GFgNqW9OS/Z+uP1rQivV9/ju7FmSkoCQ7FecuGu33c1/NZdm475jJ+NXGbt3tbiMRLNCaFma+7XD9WOe+GPD7Iybi0oMCj5roy4z7zobSrIhH9os2ptV782F6BWgM7+d/vTG8R/+R8jcmwYBg50i0tymn+HS61eu8xd5zx+WSIan8blw/AecfMMbwDrwZqUm4a0sffraiA9+fFTxoHVmaheNDzGOkBWPL8NPl7bh+bZehA1n5pgAd3DzKKGfsNwqZqUlwuwTLwxjkL5LTcMrIIpyzsBVHThsR0+MTT9gMhgzlSXbj852RPe6zSkFmKv52ynR0/Ogew9fdPCwHB3QEbs8+aUQh/vLSB1FtoygrFSfNacJP/TQRePTEqXCJhJX1wAkdHqMxoiQLh06swbaHX9M1/6jyHNNyDEdjZksJlPJ22jSTbye5sty9a+Qq89PxyRff4OooO1BnWNAhLpD64sg6tIbjoqVj0KzziZdR5o4ehlktpRF3OA92LRuWk47F7RW49L6XIi1eQOW56QHTVdYWZuDVD3YAACbWF6KmMANpyS6cEaLpmBFcLsGMAP2tonHsjKGjQButNCcNj500DV/s/Bb/+s+nupt0RXKjKCI4MECfpvj+tTGOfa6O5Dj+HpnWFmXgX//51ILSRKcw09xc14Fcd2gXqk/4g2nrj0UHLDM0lmbh+Xc/N239dUXmBd9Gts4YPGBIh08fgrmjy7BfBEOvR2tGcykm1ObjH29+gnMXjca8MWX4+ttdUT+JOXluE37/9DsBP3f6cOG+9m+LfXvgyw6KfGh3s0aujda2VePx04deQWdNftRZi/wNahX0dDapJVZOjJphZaYmITM1CQLn/WYnGgbrZKiLlo7Fvlsfxre7FG72GXUsVuK9ZthKsRpxsbksO6pgPTstKeIOXf6+Pnb4SpnZLCkcLpfgpvXd+Oqb73YPvGJE2cwctGpEcSZeen87ABjaXMFosQrSIvGDCJvORGrfAP1/fNUUZgzJFOWPiOx1ARv45682dOOaR17D/LFl8Njg6U5RViqmxnHmMIoM26yToWqLMvHYSdPw2InTLOvFbid6O3Zabesy/W2yjeDsfvn2EO79Q6Cb2IeP78flQTqvBuI7QuKAVT3VYa9Lj2humLatHI91k2rwizWdKNCeop0yt8mgkkXnlLlNEPHmf++uNWcAsWhdeUg78kweq8FXrK5JnTX5uOKQdswape/mYC8G38RX5KXjD0dONHywJjuLNlWux6eioDgrFYf314fdN8nurL+NpLgTbNj3RHDLxm58/9dPo2lYVtAho43IFRvuaHm+Ac8N67rwxc7vdOeAj1UN84ruavzm7/8Xm40lOLdLDH1icuzMBtQUZuC03z4bcJ4Utwtff7crrPX6fvUyw7jOVBV4cPJcn5FMJ9XiR394TtfygQKKKSP35A6P9MZ87aRaLBxXgTxPsm2fCs4wMMORXtHsi5jtRYNrHaY3lRg2QmysnoJGKynKG5ODu4bj8gdewUc7vsb3ZzXgsMl1u78737/1aSOKaAuJc/tGFCPjq/Nx/7FTcPnB7XAFSZERKM1YOJ2/os3p3VNXiOnNJbpz1cbK2MrcgKNDGsEpOXcjLefgtrt9IwMPrgMY3xY8MzUJK0PVrhuwyfljy3Z3OjxupvEd8k6Y3Yi0ZBdW91YHrFWuzPfgykPasaa3Blce0h7xtvIzUoYEp4GeXMRaT11B0OuYr6Xj4ys1X72J/Vv0ai3P3Z1OdNKI4OdzIEbdB5qZMjUS6SluPHDcFPz28N69AvV4w2CdIpbsSoyvz5zWCB6PRmHp+EpU5g9tv+svE0OuiQFt0LljKgAAGRpJREFUpIy6VlrReTJebFvZgYVt5ThzwShLc08HFMHvve/3Ktntwr3HTMaft/Rhs88YBEbEExsn1+GZ02fitHktQeebNaoUp85rNnQgNgCY1lgcMAPK6HJzjqkRN25FWan4zaaesJa5++i+qLdrhm0rO1CZ78Gp+zajqyYfN67bux9WrMLWlCQXfr2xBz+c34KLlvrP557IstOSMboiN24DdYDBOkVh7aQapGqDPVg1gI5ZOmvyMaHW24b09P2C/1hHKtB1JTXJjXu/N2WvaUs6KlCijdS5aJw3i0RtUQZaTfrRjkZ5bjoaS72p76YHyJlus8qZkJIcdmNaW5SJC5eO1Z0/2SlPGnylJbsxosTYNIuD2+9b2XY4ye3C3Vv6cOthPTh3Uevu6at6qrFln5FoKctGYWbK7gGD7GRcmP2VGkqzsKTDPqNlDhgY82HNxBrcvKEb3XXW9SmoL87Eiu5qXZnLrIhZR1fY77contjvLCfHyPWk4E9b+vDSe9sxuaEo9AIOUpSZissi6HRnFN8R7zoGjU55zqJWLBxXjtEVOWE9no4VEcHNG7rxxGsfYWJ9ZI9soxXtiIG+3C7BRUvH4Lq/voHVvTU44sZ/GLp+8tq2sgNXPPAKstOTcd/z7+/1mdmpG3+0YBSKs1JNH5QrHJmpSWgfnoexlbnYpYCd33yHZV1VSE1y4/dHTMQuBay4+nE88vKHVhc1apmp9ntKGIreJiHTm0pw05NvAfA2K7IbI25CIumkTvo5q7qIbGd4QQamN5dYWgMlIpimdZA0otOmHQ0OU5LdLvTWFyLLxh15c9KTsU9ziWXpBgfnk/7Zig5D1rl/WwV+s6kX88aURZ3BwAqBQl2fjHZDzB8bu+ZI05pK8OvDenCQnwFUzKgt7Kzx3gSX5aRhWWcVZrSU2q7/BuC9WVzWWYVVvTW7x04QEV1l7dRu9K2suU5LSexQ48TZTeitL8C4qlycd8AYq4szREZqEk6eE112pIq8yJuBlWbv6VRr59SqVmLNOsWFq5a349m3P3NMqkTAOU1BBgdzZg4mZKTOmnzcelg3dn6zy5RH16PKs/Hk6x8bvl67KcxMNaXN+/lLxuBIGzyduPSgNtz173cxeWSRLYN0I9ywrgsvvrcdTcPMH5V1sKtXdeCaR17Hko7KmA/OFumlNd9jTnrKHE8yrl9rzbgjeln52/nLtZ342UOvYeKIQpQF6KeR6BL7dpfiRpLbhTGVuVGlgaou2FMzMDHCHvd2N3dQZ1m9WQVuXt+NrNQklOem48TZQ2tf5ursgJs6qGnKyJLQQX807ahFBO3D89FTXxh2p6PBKf5OmN3od56zF+5pQ3zRUvNqyqy+oTOrVn1u6zCcb4MaxuKsNKzorsbwguhGvtQjUGfRaIX6jiS5XWguy45557upjSW47tAuzHNQR/H0FDcuO2gcpjYW47pDO0PO75D6Fl2s/Fvqi7Nw7uLRjvquxBpr1ok0P185Hqfc/gyq8j1Y4ifzitHC+e3U80M7eWQRHnzxv0HnOWr6CLz50RfYvvNb/HixvkEjOmvy8fjJ05Ca5PZb+7i4Xd/j9d9s6sG2h1/D9KaS3QPT2NHYylxcs2o83v/8K8wf6z9Pfn1xFv68pQ8f7fganTX52HLzv2JcSqA8z7jgb6BDcKy4XYLF7RX47+c7se3hV7Fxcl1Mtx8rt2/uxc//8ipmjSrFi+9+jp/c97LVRTLM7NZhOOX2f+Ob71TQ8SScZu7oYZirc/RUO5s/tgzn3vU8AGBWS6nFpaFoMVgn0tQXZ+Km9d1WFyNiP148Ggf//HG8rA2r7o8nJQlXRJAP2pMS5FKh86ajpSwHFy6xR9qxUI+79QwSFSgLSWqyeQ8sty5rw2m/fRZTG4vDzrgRiCDw32K2w6bUYePkWl03o05spDK2MheXav0nLnz3BYtLY6zstGTcvrkXf3/zE0emWZ1pQAA7oti+zQLLctNx/dou/POtT3DgePMrn8hcbAZDFCdKstNw2rzm0DMSZraUoqUs27BOi4f310ME2L+t3LARCP2ZN6YMT50y3RZNSIyiu3lGHOdQdqqWshwsnzDc1AHMzBLu6M8DbljbhVxPMlrLc7B2Uq3BpYpcb/2evjn7ak8GeusLsbm/3tZPMmPF6iaF0WLNOhElHJdL8LvDJ+KDHTux39ZH8O5nX0W1vmNnNmBdX21MgpZYtj1meEyH+ww45VRGjbzZU1+IJ0+ejiSXGH4uRrO68xaPwWm/fRYFGSlY1VNjXKHIFhisE1mkKIu1HVZyucTQWnC71y4GCgTsOOpf66ABVjK09J/2K2X88f0qXLx0rKHZlJLdgm++c3gVJ6wdLCuQstz0qNLU6r2XcXoNtVPZ7xtHFMcuOGAMklyCEcWZuzuxZqXtuWfuiDLHrBUX0gaT2juv6K7e/W8zc0TbefROs/PUtw/Pi9lN49Wr9AcSJdlpuOTAsdi/rRy3bAxv6HqKnO/1Y0FbuaE3c9cd2oVAGTLX9+1pUrJhcnTNS3hjR/GGNetEMbSovQJTG4uRk568e/TRm9d34+J7XsSE2gI0DXNGnvjfbOrB5fe/jOlNJablxR1ZkoVtKzvw4nvb/Q6SE+/Sk93Y2GdelpRfbeiO2RDhXTX5mNoY3sig88eW75WNJ1TMmOJ24evvdgEAaovMT8VI4ZtQW4CHj5+KU+94Fvc8995en5XmpOG2TT148b3PmcLPBEku1s06mWHBuohUAPghgFkACgC8A+B2AGcopUKOHiIiGQAWAJgLYByASgC7ALwA4EYAW5VSXxtVXiKr5GXsnYmkuSwbPzVolM1YGVeVh5+vHG/6dqY1ldhq+PdYGFeVixPnNGF4vgc5HvOa1gyM3hmMUaPkGlF7LyHqS29Y14WVVz8BT2oSTt+vJertkTnKctNRmOk/G1NbVR7aDMpyRHtzuwQXLx2L6x57A6t6qq0uDoXJkGBdROoAPAqgGMAdAJ4H0AngKACzRKRXKfVhiNVMAvBLAB8BuB/eQD8PwH4AzgewUESmKaWi6wlG5EB8rJs4RATjq0MH0mbLSU/G2kmRd1S7ank7Nv7yKaQnu3FqDLIUdVTn4/GTpyPF7UJKEmsRiXwtaCvHgjjKiZ9IjKpZvxzeQP1IpdTWgYkiciGALQDOArAxxDreBXAIgFsG16CLyLEAHgDQA2AzgAsMKjNR3LFv62tymr8c34+M1Mh/Ima2lOKh4/qR40lGtgE19HqaTmdGUV6iRKa3746d+/jEs6irH7Ra9RkAXgdwmc/HpwHYAWC51swlIKXUP5VS1/s2dVFKfY49AfqUaMtLRETB5WekGBJgV+Z7DFkPEAdPl2yYdYfsJVRTL0pcRjwr7Nfe/6SU2jX4Ay3QfgSAB8CEKLbxjfb+bRTrIHIs/s5TtBgIxKfuWuNSKxLFK7un1g3FiGC9QXt/McDnL2nvI6PYxhrt/S49M4vIU/5eABqjKAOR7TEco3jFG1b/1k+uRX9DERpLzUmhSuRUZ+zXAk+KGwd3VaEy32N1caJiRLA+kPvr0wCfD0yPaGxfETkc3gwz/wRwdSTrIEoU3XUFuzNvLBjL9GdOccTUPaNEHrNPNPUa8WtKQ/HufzM14x6pSW5cs7oTdx3dh/6GIquLo0sxB4SzHXcc3g2v7KnG06fNwFn7t1pdlKjZujeOiCwEcDG8nU8XKaW+CbEIAEAp1R5gfU/BmxaSyPYKM1PwwXZvF46O4fqygyS7XbhtUw+eeuNjTE+wlIdOdtiUOuR6UlCUlWroiJHxZFR5Ds5cMAr/eONjHDFthNXFCV8MRiw7d/FodJ51r+nbidaGyXW46cm38MH2nbho6Viri0PwpnIty0nD259+hYVBMsY4bQTTJBuONhsJI4L1gZrzQKNrDEz/JJyVisgCADcBeB9Av1Lq1ciKR+RM16+dgCsffAUT6wtRVaD/EV5FngcVec5+5BdLdvjx8aQk4dCJkadJTBTLJwzH8gnDrS6GbRVnpaGxNAvPv/t5RMvHqnI1IzUJfzm+Hx/v+AalOWmx2SgFleR24fbDe/H3Nz7e6ykW2YMRwfoL2nugZ7cDVSCB2rQPISIHALgB3hr1qUqpl0IsQhR3GkqzWOtERGFpq8rdHayXZts3EE5NcqM0x211MWiQ4qw0zBo1LKxlkt2C42Y2hJ6RomLE84H7tfcZIrLX+kQkC0AvgC8APKZnZSJyMLwjlr4NYDIDdSKi6A0e4GhZZ6WFJSEznTC7CY2lWRiWk4Ztq5w1MrJROgYNKpaWbO9mEM3Dsnf/e59m5zVdfOb0mVjfV2d1MeJe1DXrSqlXRORP8OZa3wxg66CPzwCQAeAqpdSOgYki0qgt+/zgdYnISng7kb4Bb9OXN6ItHxEReQOBH85vwXuffYX1k/jjGq9y0pPxx6MmYZfyDjGfiEaV5+CE2Y147NUPccw+9q71vfKQdlx0z4toHpbtyP4qacl8OhILRnUw3QTgUQA/EZFpAJ4D0AVvDvYXAZzsM/9z2vvuK4mI9MMbqLvgra1fLUMb0H2ilLrYoDITESUMEcGK7mqri5G4YphtQ0TgTsw4fbeNk+uwcbL9b0qrCjyOau4Yh0ljHMGQYF2rXe8A8EN40yzOAfAOgEsAnKGU+ljHaoZjT7OcNQHmeQPe7DBEREREFEOnz2vBPhc9BMCbx5xiw7DUjUqptwCs1jnvkHszpdS1AK41qjxEREREZJwRJVm49bBuvPvpTsxocV4be6eydZ51IiIiIrKPdp3jfpBx7N1NmoiIiIgogTFYJyIiIrSUBRrbkIisxGCdiIjQMTxv978njSi0sCRklZktJVg0rgJ1RRm4ef0Eq4tDRBq2WSeihDatqQQ3PvEmAGBCbeK2xbxo6Vis+5+/ITXZjdPmMctDIhIRXLBkjNXFICIfDNaJKKGdMKsRb360A19+/R0uWOKcfMdGq8z34I9HTYKf8S2IiMhCDNaJKKHleJJx/Vo+8gfAQN1EGSkc6dFKm/vrsfW+lwHAEYMlEQ3GYJ2IiMhky7uH44oHX8EnX3yD42c1Wl2chHPYlDp8+fV32KWAI6bWW10corAwWCciIjKZJyUJDx7bjzc+2oHWcmZdiTVPShJO2bfZ6mIQRYTBOhERUQzkeJIx2pNrdTGIyGGYupGIiIiIyKYYrBMRERER2RSDdSIiIiIim2KwTkRERERkUwzWiYiIiIhsisE6EREREZFNMVgnIiIiIrIpButERERERDbFYJ2IiIiIyKYYrBMRERER2RSDdSIiIiIim2KwTkRERERkUwzWiYiIiIhsisE6EREREZFNMVgnIiIiIrIpButERERERDYlSimryxAzIvJhenp6flNTk9VFISIiIqI49txzz+HLL7/8SClVEM16Ei1Yfw1ANoDXLdh8o/b+vAXbpvDxeDkLj5ez8Hg5D4+Zs/B42UM1gM+UUjXRrCShgnUrichTAKCUare6LBQaj5ez8Hg5C4+X8/CYOQuPV3xhm3UiIiIiIptisE5EREREZFMM1omIiIiIbIrBOhERERGRTTFYJyIiIiKyKWaDISIiIiKyKdasExERERHZFIN1IiIiIiKbYrBORERERGRTDNaJiIiIiGyKwToRERERkU0xWCciIiIisikG60RERERENsVg3WQiUiEiV4vI2yKyU0ReF5GLRSTP6rLFA21/qgCvdwMs0yMid4rIRyLypYg8LSJHi4g7yHb2FZEHRORTEdkuIo+LyMoQZVspIk9o83+qLb9vtH+z3YnIYhHZKiJ/EZHPtGPxyxDL2PKYiIhbRLZo5flSK9+dItITek84RzjHTESqg5xzSkRuCrId0/e/iKSLyBki8oKIfCUi74vIr0SkKby9Yk8iUiAia0XkNhF5Wdsvn4rIwyJyqIj4/V3nOWaNcI8Xzy/ySynFl0kvAHUA3gOgANwO4BwA92n/fx5AgdVldPoLwOsAPgFwup/XsX7mnw/gWwDbAWwDcJ52LBSAWwJs43Dt8w8AXAbgIgBvadPOD7DM+drnb2nzXwbgQ23a4VbvN5OPyT+1v/NzAM9p//5lkPlteUwACIBbBp2v52nl266Vd77V+9qKYwagWvv8nwHOu8VW7X8AqQAe1pZ5EsC5AG4A8A2AHQC6rN7XBhyrjdrf9zaA6wGcDeBqeK+DCsCvoQ14OGgZnmMOOV48v/jye3ytLkA8vwDcrX2pj/CZfqE2/Uqry+j0F7zB+us6580G8D6AnQA6Bk1PA/CodkwO9FmmGsBX2kWvetD0PAAva8t0+yzTo01/GUCez7o+1NZXHc7f6aQXgH4AI7QfgykIHvjZ9pgAWKYt8wiAtEHTx2vlfR9AltX724JjVq19fm0Y64/J/gdworbMLQBcg6bP16Y/O3i6E18ApgKY5/t3ACgF8Kb2dy4aNJ3nmLOOF88vvoYeY6sLEK8veGvVFYDX/JykWfDeve4AkGF1WZ38QnjB+hrtmPzCz2dTtc8e9Jn+Q236GXrXB+B/tOmr/SwTcH3x+ELowM+2xwTAQ9r0fj/LBFyf0186jlkkwYTp+x/eG403tOk1fpYJuL54eQE4Sfsbtw6axnPMpq8Ax4vnF19DXmyzbp5+7f1PSqldgz9QSn0O792sB8CEWBcsDqWKyCEicpKIHCUi/QHaYU7V3u/y89lDAL4A0CMiqTqX+aPPPNEsk6hseUxEJA3e2qovAPwljO0kkjIR2aCddxtEZHSQeWOx/+sAVAF4USn1ms5l4s032vu3g6bxHLMvf8drAM8v2i3J6gLEsQbt/cUAn78EYAaAkQDujUmJ4lcpgOt8pr0mIquVUg8OmhbwmCilvhWR1wC0AKiFt91uqGXeEZEdACpExKOU+kJEMgCUA9iulHrHT1lf0t5H6vnDEoBdj0kdADeAV5VS/n5IeRyBfbTXbiLyAICVSqk3B02L1f7Xc831XSZuiEgSgBXafwcHbTzHbCjI8RrA84t2Y826eXK0908DfD4wPTcGZYln1wCYBm/AngGgFcBV8D5K/KOIjBk0byTHRO8yOT7vPO762PWY8DgG9gWAMwG0w9uGOQ/AZAD3w9uE5l4tgBgQq/2f6MfsHACjANyplLp70HSeY/YU6Hjx/KIhGKyToymlzlBK3aeUek8p9YVS6t9KqY3wduJNh7f3PBEZRCn1vlLqVKXU35VSn2ivh+B9Uvg4gHoAa60tZWIRkSMBHANvVo/lFheHQgh2vHh+kT8M1s3jW/Pga2D6JzEoSyK6UnvvGzQtkmOid5lPfd553PWx6zHhcQyT9jj959p/Y3XeJfwxE5HDAVwC4H/h7dz3kc8sPMdsRMfx8ovnV2JjsG6eF7T3QO23Rmjvgdp/UXT+q70PflwY8Jho7Qdr4O3o86rOZYZp6/+PUuoLAFBK7QDwfwAytc998bjvza7H5BUA3wGo1cqhZxnyc97FcP8n3DVXRI4GsBXAv+EN/PwNBMdzzCZ0Hq9geH4lKAbr5rlfe5/hZ4SyLAC98LZNeyzWBUsQA1l2Bv8A3ae9z/Izfx+82XkeVUrt1LnMbJ95olkmUdnymCilvoI3B7UHwKQwtpPo/J13QGz2/yvw5q0eKSI1OpdxLBE5Ht7Bb/4Jb+D3foBZeY7ZQBjHKxieX4nK6tyR8fwCB0Uye/82wU+eeng7l76k7eOTBk3PhrdmIpzBQWrAQZGiOUZTEHpQJFseE+gbNCTb6n1swTEbBz8Dn8Db0fsrbdkeK/Y/EmTQFgA/0P6evwHIDzEvzzFnHS+eX3wNeYm2o8kEIlIH78WwGMAd8KbF6oI3B/uL8J5wH1pXQmcTkdPh7aTzELyDNXwOb0qqufD+EN0JYH+l1NeDllkA7/DOXwG4CcBHAPaDNy3VrwEsUT4nhYgcAeAn8F70bgbwNYDFACoAXKCUOtZP2S4A8D0A/9HWmwJgKYACeG/eLjViH9iRto8XaP8tBTAT3pqggXy+HwzeZ3Y9JiIiAH6lrfd5AL/T5l0K7/drkVLqjvD2jj2Fc8y09HEj4L22/Uf7fDT25Ff+gVLqR362Yfr+13KF3wdv8PI3eNPiVgE4AN7vyFSl1OP694z9iMhKANfC24xhK/xn53hdKXXtoGV4jlkk3OPF84v8svpuId5fACrhTS/4Drxf5jcAXIxBd798RbxvJwO4Ed4LzSfwDjDxXwB/hjd/rQRYrhfeQP5jAF8CeAbAFgDuINuaB+BBeG8IdgB4Et58t8HKt0qbb4e23IMA9rV6v8XguJwOby1LoNfrTjkm8I5FsUUrz5da+e6ET82W01/hHDMAhwL4PbyjB2+HtxbuTXgDuklW7394H+3/EN6nazu1a8ItAJqt3s8xOlYKwAN+luM55oDjxfOLL38v1qwTEREREdkUO5gSEREREdkUg3UiIiIiIptisE5EREREZFMM1omIiIiIbIrBOhERERGRTTFYJyIiIiKyKQbrREREREQ2xWCdiIiIiMimGKwTEREREdkUg3UiIiIiIptisE5EREREZFMM1omIiIiIbIrBOhERERGRTTFYJyIiIiKyKQbrREREREQ2xWCdiIiIiMimGKwTEREREdnU/we+PKGYYaqEEQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 250,
       "width": 373
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(ctr_net.losses['train'], label='Training loss')\n",
    "plt.legend()\n",
    "_ = plt.ylim()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 250,
       "width": 373
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(ctr_net.losses['test'], label='Test loss')\n",
    "plt.legend()\n",
    "_ = plt.ylim()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 使用测试数据进行测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "ffm_test_out_path = './te_ffm.out.logit'\n",
    "fm_test_out_path = './te.fm.logits'\n",
    "test_path = './data/test.txt'\n",
    "\n",
    "ffm_test = pd.read_csv(ffm_test_out_path, header=None)    \n",
    "ffm_test = ffm_test[0].values\n",
    "\n",
    "fm_test = pd.read_csv(fm_test_out_path, header=None)    \n",
    "fm_test = fm_test[0].values\n",
    "\n",
    "test_data = pd.read_csv(test_path, header=None)    \n",
    "test_data = test_data.values\n",
    "\n",
    "pred_test_X = np.concatenate((ffm_test.reshape(-1, 1), fm_test.reshape(-1, 1), test_data), 1).astype(np.float32)\n",
    "\n",
    "# pred_test_X = cc_test[:,0:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "save_params_with_name((pred_test_X), \"pred_test_X\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pred_test_X = load_params_with_name(\"pred_test_X\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000000"
      ]
     },
     "execution_count": 275,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pred_test_X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_9\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "sparse_input (InputLayer)       [(None, 26)]         0                                            \n",
      "__________________________________________________________________________________________________\n",
      "embedding_9 (Embedding)         (None, 26, 32)       960000      sparse_input[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "dense_input (InputLayer)        [(None, 13)]         0                                            \n",
      "__________________________________________________________________________________________________\n",
      "reshape_9 (Reshape)             (None, 832)          0           embedding_9[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_18 (Concatenate)    (None, 845)          0           dense_input[0][0]                \n",
      "                                                                 reshape_9[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "fc1_layer (Dense)               (None, 400)          338400      concatenate_18[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "FFM_input (InputLayer)          [(None, 1)]          0                                            \n",
      "__________________________________________________________________________________________________\n",
      "FM_input (InputLayer)           [(None, 1)]          0                                            \n",
      "__________________________________________________________________________________________________\n",
      "fc2_layer (Dense)               (None, 400)          160400      fc1_layer[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "ffm_fc_layer (Dense)            (None, 1)            2           FFM_input[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "fm_fc_layer (Dense)             (None, 1)            2           FM_input[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "fc3_layer (Dense)               (None, 400)          160400      fc2_layer[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_19 (Concatenate)    (None, 402)          0           ffm_fc_layer[0][0]               \n",
      "                                                                 fm_fc_layer[0][0]                \n",
      "                                                                 fc3_layer[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "logits_layer (Dense)            (None, 1)            403         concatenate_19[0][0]             \n",
      "==================================================================================================\n",
      "Total params: 1,619,607\n",
      "Trainable params: 1,619,607\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "ctr_net=ctr_network(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 下采样训练的网络预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0]], dtype=int32)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ctr_net.predict_click(pred_test_X[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0],\n",
       "       [0],\n",
       "       [0],\n",
       "       [1],\n",
       "       [0],\n",
       "       [0],\n",
       "       [1],\n",
       "       [0],\n",
       "       [0],\n",
       "       [1],\n",
       "       [0],\n",
       "       [0],\n",
       "       [1],\n",
       "       [1],\n",
       "       [0],\n",
       "       [0],\n",
       "       [0],\n",
       "       [1],\n",
       "       [1],\n",
       "       [0]], dtype=int32)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ctr_net.predict_click(pred_test_X[:20], 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 全数据训练的网络预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0]], dtype=int32)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ctr_net.predict_click(pred_test_X[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0],\n",
       "       [0],\n",
       "       [0],\n",
       "       [0],\n",
       "       [0],\n",
       "       [0],\n",
       "       [0],\n",
       "       [0],\n",
       "       [0],\n",
       "       [0],\n",
       "       [0],\n",
       "       [0],\n",
       "       [1],\n",
       "       [1],\n",
       "       [0],\n",
       "       [0],\n",
       "       [0],\n",
       "       [1],\n",
       "       [1],\n",
       "       [0]], dtype=int32)"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ctr_net.predict_click(pred_test_X[:20], 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_test_batches(Xs, batch_size):\n",
    "    for start in range(0, len(Xs), batch_size):\n",
    "        end = min(start + batch_size, len(Xs))\n",
    "        yield Xs[start:end]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict_test(ctr_net, batch_size, axis = 1):\n",
    "    if True:\n",
    "        test_batches = get_test_batches(pred_test_X, batch_size)\n",
    "        total_num = len(pred_test_X)\n",
    "        \n",
    "        pred_lst = []\n",
    "        for batch_i in range(total_num // batch_size):\n",
    "            x = next(test_batches)\n",
    "            # Get Prediction\n",
    "            clicked = ctr_net.predict_click(x, axis)\n",
    "            pred_lst.append(clicked)\n",
    "            if ((total_num // batch_size) + batch_i) % show_every_n_batches == 0:\n",
    "                        print('Batch {:>4}/{}   mean click = {}'.format(\n",
    "                            batch_i,\n",
    "                            (total_num // batch_size),\n",
    "                            np.mean(np.array(clicked))))\n",
    "#         print(np.array(clicked))\n",
    "        return pred_lst"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 下采样训练的网络预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Batch    0/15625   mean click = 0.328125\n",
      "Batch   25/15625   mean click = 0.359375\n",
      "Batch   50/15625   mean click = 0.296875\n",
      "Batch   75/15625   mean click = 0.28125\n",
      "Batch  100/15625   mean click = 0.4375\n",
      "Batch  125/15625   mean click = 0.328125\n",
      "Batch  150/15625   mean click = 0.21875\n",
      "Batch  175/15625   mean click = 0.390625\n",
      "Batch  200/15625   mean click = 0.328125\n",
      "Batch  225/15625   mean click = 0.359375\n",
      "Batch  250/15625   mean click = 0.328125\n",
      "Batch  275/15625   mean click = 0.265625\n",
      "Batch  300/15625   mean click = 0.390625\n",
      "Batch  325/15625   mean click = 0.40625\n",
      "Batch  350/15625   mean click = 0.328125\n",
      "Batch  375/15625   mean click = 0.296875\n",
      "Batch  400/15625   mean click = 0.359375\n",
      "Batch  425/15625   mean click = 0.390625\n",
      "Batch  450/15625   mean click = 0.4375\n",
      "Batch  475/15625   mean click = 0.359375\n",
      "Batch  500/15625   mean click = 0.328125\n",
      "Batch  525/15625   mean click = 0.421875\n",
      "Batch  550/15625   mean click = 0.375\n",
      "Batch  575/15625   mean click = 0.34375\n",
      "Batch  600/15625   mean click = 0.296875\n",
      "Batch  625/15625   mean click = 0.375\n",
      "Batch  650/15625   mean click = 0.375\n",
      "Batch  675/15625   mean click = 0.34375\n",
      "Batch  700/15625   mean click = 0.359375\n",
      "Batch  725/15625   mean click = 0.3125\n",
      "Batch  750/15625   mean click = 0.3125\n",
      "Batch  775/15625   mean click = 0.4375\n",
      "Batch  800/15625   mean click = 0.4375\n",
      "Batch  825/15625   mean click = 0.328125\n",
      "Batch  850/15625   mean click = 0.53125\n",
      "Batch  875/15625   mean click = 0.40625\n",
      "Batch  900/15625   mean click = 0.390625\n",
      "Batch  925/15625   mean click = 0.40625\n",
      "Batch  950/15625   mean click = 0.421875\n",
      "Batch  975/15625   mean click = 0.40625\n",
      "Batch 1000/15625   mean click = 0.3125\n",
      "Batch 1025/15625   mean click = 0.265625\n",
      "Batch 1050/15625   mean click = 0.421875\n",
      "Batch 1075/15625   mean click = 0.296875\n",
      "Batch 1100/15625   mean click = 0.453125\n",
      "Batch 1125/15625   mean click = 0.265625\n",
      "Batch 1150/15625   mean click = 0.359375\n",
      "Batch 1175/15625   mean click = 0.375\n",
      "Batch 1200/15625   mean click = 0.3125\n",
      "Batch 1225/15625   mean click = 0.328125\n",
      "Batch 1250/15625   mean click = 0.296875\n",
      "Batch 1275/15625   mean click = 0.296875\n",
      "Batch 1300/15625   mean click = 0.3125\n",
      "Batch 1325/15625   mean click = 0.359375\n",
      "Batch 1350/15625   mean click = 0.40625\n",
      "Batch 1375/15625   mean click = 0.375\n",
      "Batch 1400/15625   mean click = 0.4375\n",
      "Batch 1425/15625   mean click = 0.296875\n",
      "Batch 1450/15625   mean click = 0.296875\n",
      "Batch 1475/15625   mean click = 0.34375\n",
      "Batch 1500/15625   mean click = 0.5\n",
      "Batch 1525/15625   mean click = 0.4375\n",
      "Batch 1550/15625   mean click = 0.40625\n",
      "Batch 1575/15625   mean click = 0.40625\n",
      "Batch 1600/15625   mean click = 0.34375\n",
      "Batch 1625/15625   mean click = 0.390625\n",
      "Batch 1650/15625   mean click = 0.515625\n",
      "Batch 1675/15625   mean click = 0.34375\n",
      "Batch 1700/15625   mean click = 0.484375\n",
      "Batch 1725/15625   mean click = 0.375\n",
      "Batch 1750/15625   mean click = 0.390625\n",
      "Batch 1775/15625   mean click = 0.515625\n",
      "Batch 1800/15625   mean click = 0.390625\n",
      "Batch 1825/15625   mean click = 0.359375\n",
      "Batch 1850/15625   mean click = 0.421875\n",
      "Batch 1875/15625   mean click = 0.34375\n",
      "Batch 1900/15625   mean click = 0.484375\n",
      "Batch 1925/15625   mean click = 0.375\n",
      "Batch 1950/15625   mean click = 0.40625\n",
      "Batch 1975/15625   mean click = 0.5\n",
      "Batch 2000/15625   mean click = 0.515625\n",
      "Batch 2025/15625   mean click = 0.515625\n",
      "Batch 2050/15625   mean click = 0.421875\n",
      "Batch 2075/15625   mean click = 0.46875\n",
      "Batch 2100/15625   mean click = 0.484375\n",
      "Batch 2125/15625   mean click = 0.421875\n",
      "Batch 2150/15625   mean click = 0.46875\n",
      "Batch 2175/15625   mean click = 0.40625\n",
      "Batch 2200/15625   mean click = 0.453125\n",
      "Batch 2225/15625   mean click = 0.390625\n",
      "Batch 2250/15625   mean click = 0.40625\n",
      "Batch 2275/15625   mean click = 0.453125\n",
      "Batch 2300/15625   mean click = 0.53125\n",
      "Batch 2325/15625   mean click = 0.46875\n",
      "Batch 2350/15625   mean click = 0.484375\n",
      "Batch 2375/15625   mean click = 0.46875\n",
      "Batch 2400/15625   mean click = 0.375\n",
      "Batch 2425/15625   mean click = 0.4375\n",
      "Batch 2450/15625   mean click = 0.34375\n",
      "Batch 2475/15625   mean click = 0.5\n",
      "Batch 2500/15625   mean click = 0.515625\n",
      "Batch 2525/15625   mean click = 0.40625\n",
      "Batch 2550/15625   mean click = 0.4375\n",
      "Batch 2575/15625   mean click = 0.4375\n",
      "Batch 2600/15625   mean click = 0.4375\n",
      "Batch 2625/15625   mean click = 0.46875\n",
      "Batch 2650/15625   mean click = 0.546875\n",
      "Batch 2675/15625   mean click = 0.4375\n",
      "Batch 2700/15625   mean click = 0.3125\n",
      "Batch 2725/15625   mean click = 0.46875\n",
      "Batch 2750/15625   mean click = 0.46875\n",
      "Batch 2775/15625   mean click = 0.4375\n",
      "Batch 2800/15625   mean click = 0.46875\n",
      "Batch 2825/15625   mean click = 0.5625\n",
      "Batch 2850/15625   mean click = 0.484375\n",
      "Batch 2875/15625   mean click = 0.484375\n",
      "Batch 2900/15625   mean click = 0.421875\n",
      "Batch 2925/15625   mean click = 0.515625\n",
      "Batch 2950/15625   mean click = 0.453125\n",
      "Batch 2975/15625   mean click = 0.453125\n",
      "Batch 3000/15625   mean click = 0.515625\n",
      "Batch 3025/15625   mean click = 0.53125\n",
      "Batch 3050/15625   mean click = 0.5\n",
      "Batch 3075/15625   mean click = 0.328125\n",
      "Batch 3100/15625   mean click = 0.359375\n",
      "Batch 3125/15625   mean click = 0.5\n",
      "Batch 3150/15625   mean click = 0.453125\n",
      "Batch 3175/15625   mean click = 0.453125\n",
      "Batch 3200/15625   mean click = 0.34375\n",
      "Batch 3225/15625   mean click = 0.46875\n",
      "Batch 3250/15625   mean click = 0.390625\n",
      "Batch 3275/15625   mean click = 0.421875\n",
      "Batch 3300/15625   mean click = 0.421875\n",
      "Batch 3325/15625   mean click = 0.453125\n",
      "Batch 3350/15625   mean click = 0.5625\n",
      "Batch 3375/15625   mean click = 0.453125\n",
      "Batch 3400/15625   mean click = 0.40625\n",
      "Batch 3425/15625   mean click = 0.390625\n",
      "Batch 3450/15625   mean click = 0.453125\n",
      "Batch 3475/15625   mean click = 0.5625\n",
      "Batch 3500/15625   mean click = 0.421875\n",
      "Batch 3525/15625   mean click = 0.453125\n",
      "Batch 3550/15625   mean click = 0.46875\n",
      "Batch 3575/15625   mean click = 0.453125\n",
      "Batch 3600/15625   mean click = 0.4375\n",
      "Batch 3625/15625   mean click = 0.390625\n",
      "Batch 3650/15625   mean click = 0.578125\n",
      "Batch 3675/15625   mean click = 0.296875\n",
      "Batch 3700/15625   mean click = 0.53125\n",
      "Batch 3725/15625   mean click = 0.453125\n",
      "Batch 3750/15625   mean click = 0.546875\n",
      "Batch 3775/15625   mean click = 0.453125\n",
      "Batch 3800/15625   mean click = 0.375\n",
      "Batch 3825/15625   mean click = 0.4375\n",
      "Batch 3850/15625   mean click = 0.40625\n",
      "Batch 3875/15625   mean click = 0.375\n",
      "Batch 3900/15625   mean click = 0.546875\n",
      "Batch 3925/15625   mean click = 0.421875\n",
      "Batch 3950/15625   mean click = 0.4375\n",
      "Batch 3975/15625   mean click = 0.4375\n",
      "Batch 4000/15625   mean click = 0.40625\n",
      "Batch 4025/15625   mean click = 0.390625\n",
      "Batch 4050/15625   mean click = 0.359375\n",
      "Batch 4075/15625   mean click = 0.3125\n",
      "Batch 4100/15625   mean click = 0.421875\n",
      "Batch 4125/15625   mean click = 0.53125\n",
      "Batch 4150/15625   mean click = 0.421875\n",
      "Batch 4175/15625   mean click = 0.4375\n",
      "Batch 4200/15625   mean click = 0.546875\n",
      "Batch 4225/15625   mean click = 0.515625\n",
      "Batch 4250/15625   mean click = 0.421875\n",
      "Batch 4275/15625   mean click = 0.375\n",
      "Batch 4300/15625   mean click = 0.5\n",
      "Batch 4325/15625   mean click = 0.46875\n",
      "Batch 4350/15625   mean click = 0.53125\n",
      "Batch 4375/15625   mean click = 0.515625\n",
      "Batch 4400/15625   mean click = 0.53125\n",
      "Batch 4425/15625   mean click = 0.515625\n",
      "Batch 4450/15625   mean click = 0.5\n",
      "Batch 4475/15625   mean click = 0.40625\n",
      "Batch 4500/15625   mean click = 0.28125\n",
      "Batch 4525/15625   mean click = 0.359375\n",
      "Batch 4550/15625   mean click = 0.546875\n",
      "Batch 4575/15625   mean click = 0.40625\n",
      "Batch 4600/15625   mean click = 0.46875\n",
      "Batch 4625/15625   mean click = 0.40625\n",
      "Batch 4650/15625   mean click = 0.515625\n",
      "Batch 4675/15625   mean click = 0.40625\n",
      "Batch 4700/15625   mean click = 0.515625\n",
      "Batch 4725/15625   mean click = 0.375\n",
      "Batch 4750/15625   mean click = 0.375\n",
      "Batch 4775/15625   mean click = 0.34375\n",
      "Batch 4800/15625   mean click = 0.53125\n",
      "Batch 4825/15625   mean click = 0.4375\n",
      "Batch 4850/15625   mean click = 0.46875\n",
      "Batch 4875/15625   mean click = 0.375\n",
      "Batch 4900/15625   mean click = 0.46875\n",
      "Batch 4925/15625   mean click = 0.4375\n",
      "Batch 4950/15625   mean click = 0.40625\n",
      "Batch 4975/15625   mean click = 0.46875\n",
      "Batch 5000/15625   mean click = 0.484375\n",
      "Batch 5025/15625   mean click = 0.421875\n",
      "Batch 5050/15625   mean click = 0.40625\n",
      "Batch 5075/15625   mean click = 0.59375\n",
      "Batch 5100/15625   mean click = 0.5\n",
      "Batch 5125/15625   mean click = 0.375\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Batch 5150/15625   mean click = 0.375\n",
      "Batch 5175/15625   mean click = 0.453125\n",
      "Batch 5200/15625   mean click = 0.59375\n",
      "Batch 5225/15625   mean click = 0.390625\n",
      "Batch 5250/15625   mean click = 0.46875\n",
      "Batch 5275/15625   mean click = 0.5\n",
      "Batch 5300/15625   mean click = 0.40625\n",
      "Batch 5325/15625   mean click = 0.5\n",
      "Batch 5350/15625   mean click = 0.390625\n",
      "Batch 5375/15625   mean click = 0.5\n",
      "Batch 5400/15625   mean click = 0.4375\n",
      "Batch 5425/15625   mean click = 0.359375\n",
      "Batch 5450/15625   mean click = 0.5\n",
      "Batch 5475/15625   mean click = 0.46875\n",
      "Batch 5500/15625   mean click = 0.46875\n",
      "Batch 5525/15625   mean click = 0.390625\n",
      "Batch 5550/15625   mean click = 0.328125\n",
      "Batch 5575/15625   mean click = 0.421875\n",
      "Batch 5600/15625   mean click = 0.421875\n",
      "Batch 5625/15625   mean click = 0.4375\n",
      "Batch 5650/15625   mean click = 0.4375\n",
      "Batch 5675/15625   mean click = 0.5\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Batch 15275/15625   mean click = 0.40625\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Batch 15300/15625   mean click = 0.40625\n",
      "Batch 15325/15625   mean click = 0.359375\n",
      "Batch 15350/15625   mean click = 0.4375\n",
      "Batch 15375/15625   mean click = 0.328125\n",
      "Batch 15400/15625   mean click = 0.34375\n",
      "Batch 15425/15625   mean click = 0.421875\n",
      "Batch 15450/15625   mean click = 0.5\n",
      "Batch 15475/15625   mean click = 0.375\n",
      "Batch 15500/15625   mean click = 0.515625\n",
      "Batch 15525/15625   mean click = 0.515625\n",
      "Batch 15550/15625   mean click = 0.375\n",
      "Batch 15575/15625   mean click = 0.4375\n",
      "Batch 15600/15625   mean click = 0.359375\n"
     ]
    }
   ],
   "source": [
    "pred_lst = predict_test(ctr_net, 64)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.429097"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(pred_lst)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 全数据训练的网络预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Batch    0/15625   mean click = 0.140625\n",
      "Batch   25/15625   mean click = 0.1875\n",
      "Batch   50/15625   mean click = 0.078125\n",
      "Batch   75/15625   mean click = 0.15625\n",
      "Batch  100/15625   mean click = 0.078125\n",
      "Batch  125/15625   mean click = 0.109375\n",
      "Batch  150/15625   mean click = 0.03125\n",
      "Batch  175/15625   mean click = 0.109375\n",
      "Batch  200/15625   mean click = 0.125\n",
      "Batch  225/15625   mean click = 0.125\n",
      "Batch  250/15625   mean click = 0.046875\n",
      "Batch  275/15625   mean click = 0.046875\n",
      "Batch  300/15625   mean click = 0.15625\n",
      "Batch  325/15625   mean click = 0.15625\n",
      "Batch  350/15625   mean click = 0.09375\n",
      "Batch  375/15625   mean click = 0.109375\n",
      "Batch  400/15625   mean click = 0.125\n",
      "Batch  425/15625   mean click = 0.09375\n",
      "Batch  450/15625   mean click = 0.21875\n",
      "Batch  475/15625   mean click = 0.171875\n",
      "Batch  500/15625   mean click = 0.0625\n",
      "Batch  525/15625   mean click = 0.0625\n",
      "Batch  550/15625   mean click = 0.109375\n",
      "Batch  575/15625   mean click = 0.078125\n",
      "Batch  600/15625   mean click = 0.125\n",
      "Batch  625/15625   mean click = 0.125\n",
      "Batch  650/15625   mean click = 0.140625\n",
      "Batch  675/15625   mean click = 0.09375\n",
      "Batch  700/15625   mean click = 0.125\n",
      "Batch  725/15625   mean click = 0.0625\n",
      "Batch  750/15625   mean click = 0.171875\n",
      "Batch  775/15625   mean click = 0.21875\n",
      "Batch  800/15625   mean click = 0.078125\n",
      "Batch  825/15625   mean click = 0.078125\n",
      "Batch  850/15625   mean click = 0.140625\n",
      "Batch  875/15625   mean click = 0.171875\n",
      "Batch  900/15625   mean click = 0.109375\n",
      "Batch  925/15625   mean click = 0.125\n",
      "Batch  950/15625   mean click = 0.1875\n",
      "Batch  975/15625   mean click = 0.1875\n",
      "Batch 1000/15625   mean click = 0.125\n",
      "Batch 1025/15625   mean click = 0.15625\n",
      "Batch 1050/15625   mean click = 0.1875\n",
      "Batch 1075/15625   mean click = 0.09375\n",
      "Batch 1100/15625   mean click = 0.109375\n",
      "Batch 1125/15625   mean click = 0.125\n",
      "Batch 1150/15625   mean click = 0.078125\n",
      "Batch 1175/15625   mean click = 0.09375\n",
      "Batch 1200/15625   mean click = 0.125\n",
      "Batch 1225/15625   mean click = 0.1875\n",
      "Batch 1250/15625   mean click = 0.078125\n",
      "Batch 1275/15625   mean click = 0.09375\n",
      "Batch 1300/15625   mean click = 0.046875\n",
      "Batch 1325/15625   mean click = 0.15625\n",
      "Batch 1350/15625   mean click = 0.125\n",
      "Batch 1375/15625   mean click = 0.09375\n",
      "Batch 1400/15625   mean click = 0.140625\n",
      "Batch 1425/15625   mean click = 0.046875\n",
      "Batch 1450/15625   mean click = 0.109375\n",
      "Batch 1475/15625   mean click = 0.09375\n",
      "Batch 1500/15625   mean click = 0.234375\n",
      "Batch 1525/15625   mean click = 0.140625\n",
      "Batch 1550/15625   mean click = 0.125\n",
      "Batch 1575/15625   mean click = 0.15625\n",
      "Batch 1600/15625   mean click = 0.203125\n",
      "Batch 1625/15625   mean click = 0.140625\n",
      "Batch 1650/15625   mean click = 0.1875\n",
      "Batch 1675/15625   mean click = 0.203125\n",
      "Batch 1700/15625   mean click = 0.234375\n",
      "Batch 1725/15625   mean click = 0.171875\n",
      "Batch 1750/15625   mean click = 0.09375\n",
      "Batch 1775/15625   mean click = 0.109375\n",
      "Batch 1800/15625   mean click = 0.15625\n",
      "Batch 1825/15625   mean click = 0.125\n",
      "Batch 1850/15625   mean click = 0.25\n",
      "Batch 1875/15625   mean click = 0.09375\n",
      "Batch 1900/15625   mean click = 0.234375\n",
      "Batch 1925/15625   mean click = 0.140625\n",
      "Batch 1950/15625   mean click = 0.15625\n",
      "Batch 1975/15625   mean click = 0.296875\n",
      "Batch 2000/15625   mean click = 0.1875\n",
      "Batch 2025/15625   mean click = 0.25\n",
      "Batch 2050/15625   mean click = 0.125\n",
      "Batch 2075/15625   mean click = 0.125\n",
      "Batch 2100/15625   mean click = 0.1875\n",
      "Batch 2125/15625   mean click = 0.171875\n",
      "Batch 2150/15625   mean click = 0.1875\n",
      "Batch 2175/15625   mean click = 0.09375\n",
      "Batch 2200/15625   mean click = 0.203125\n",
      "Batch 2225/15625   mean click = 0.125\n",
      "Batch 2250/15625   mean click = 0.078125\n",
      "Batch 2275/15625   mean click = 0.171875\n",
      "Batch 2300/15625   mean click = 0.1875\n",
      "Batch 2325/15625   mean click = 0.171875\n",
      "Batch 2350/15625   mean click = 0.140625\n",
      "Batch 2375/15625   mean click = 0.15625\n",
      "Batch 2400/15625   mean click = 0.09375\n",
      "Batch 2425/15625   mean click = 0.15625\n",
      "Batch 2450/15625   mean click = 0.09375\n",
      "Batch 2475/15625   mean click = 0.1875\n",
      "Batch 2500/15625   mean click = 0.15625\n",
      "Batch 2525/15625   mean click = 0.140625\n",
      "Batch 2550/15625   mean click = 0.171875\n",
      "Batch 2575/15625   mean click = 0.15625\n",
      "Batch 2600/15625   mean click = 0.15625\n",
      "Batch 2625/15625   mean click = 0.171875\n",
      "Batch 2650/15625   mean click = 0.171875\n",
      "Batch 2675/15625   mean click = 0.203125\n",
      "Batch 2700/15625   mean click = 0.09375\n",
      "Batch 2725/15625   mean click = 0.140625\n",
      "Batch 2750/15625   mean click = 0.15625\n",
      "Batch 2775/15625   mean click = 0.109375\n",
      "Batch 2800/15625   mean click = 0.171875\n",
      "Batch 2825/15625   mean click = 0.171875\n",
      "Batch 2850/15625   mean click = 0.15625\n",
      "Batch 2875/15625   mean click = 0.171875\n",
      "Batch 2900/15625   mean click = 0.078125\n",
      "Batch 2925/15625   mean click = 0.171875\n",
      "Batch 2950/15625   mean click = 0.125\n",
      "Batch 2975/15625   mean click = 0.15625\n",
      "Batch 3000/15625   mean click = 0.15625\n",
      "Batch 3025/15625   mean click = 0.140625\n",
      "Batch 3050/15625   mean click = 0.140625\n",
      "Batch 3075/15625   mean click = 0.1875\n",
      "Batch 3100/15625   mean click = 0.125\n",
      "Batch 3125/15625   mean click = 0.234375\n",
      "Batch 3150/15625   mean click = 0.234375\n",
      "Batch 3175/15625   mean click = 0.1875\n",
      "Batch 3200/15625   mean click = 0.109375\n",
      "Batch 3225/15625   mean click = 0.078125\n",
      "Batch 3250/15625   mean click = 0.140625\n",
      "Batch 3275/15625   mean click = 0.21875\n",
      "Batch 3300/15625   mean click = 0.15625\n",
      "Batch 3325/15625   mean click = 0.140625\n",
      "Batch 3350/15625   mean click = 0.1875\n",
      "Batch 3375/15625   mean click = 0.15625\n",
      "Batch 3400/15625   mean click = 0.109375\n",
      "Batch 3425/15625   mean click = 0.171875\n",
      "Batch 3450/15625   mean click = 0.1875\n",
      "Batch 3475/15625   mean click = 0.109375\n",
      "Batch 3500/15625   mean click = 0.15625\n",
      "Batch 3525/15625   mean click = 0.15625\n",
      "Batch 3550/15625   mean click = 0.09375\n",
      "Batch 3575/15625   mean click = 0.140625\n",
      "Batch 3600/15625   mean click = 0.1875\n",
      "Batch 3625/15625   mean click = 0.203125\n",
      "Batch 3650/15625   mean click = 0.15625\n",
      "Batch 3675/15625   mean click = 0.09375\n",
      "Batch 3700/15625   mean click = 0.21875\n",
      "Batch 3725/15625   mean click = 0.234375\n",
      "Batch 3750/15625   mean click = 0.1875\n",
      "Batch 3775/15625   mean click = 0.171875\n",
      "Batch 3800/15625   mean click = 0.15625\n",
      "Batch 3825/15625   mean click = 0.140625\n",
      "Batch 3850/15625   mean click = 0.203125\n",
      "Batch 3875/15625   mean click = 0.078125\n",
      "Batch 3900/15625   mean click = 0.203125\n",
      "Batch 3925/15625   mean click = 0.15625\n",
      "Batch 3950/15625   mean click = 0.109375\n",
      "Batch 3975/15625   mean click = 0.140625\n",
      "Batch 4000/15625   mean click = 0.1875\n",
      "Batch 4025/15625   mean click = 0.125\n",
      "Batch 4050/15625   mean click = 0.09375\n",
      "Batch 4075/15625   mean click = 0.046875\n",
      "Batch 4100/15625   mean click = 0.21875\n",
      "Batch 4125/15625   mean click = 0.15625\n",
      "Batch 4150/15625   mean click = 0.171875\n",
      "Batch 4175/15625   mean click = 0.140625\n",
      "Batch 4200/15625   mean click = 0.234375\n",
      "Batch 4225/15625   mean click = 0.171875\n",
      "Batch 4250/15625   mean click = 0.15625\n",
      "Batch 4275/15625   mean click = 0.078125\n",
      "Batch 4300/15625   mean click = 0.171875\n",
      "Batch 4325/15625   mean click = 0.1875\n",
      "Batch 4350/15625   mean click = 0.171875\n",
      "Batch 4375/15625   mean click = 0.203125\n",
      "Batch 4400/15625   mean click = 0.234375\n",
      "Batch 4425/15625   mean click = 0.1875\n",
      "Batch 4450/15625   mean click = 0.25\n",
      "Batch 4475/15625   mean click = 0.15625\n",
      "Batch 4500/15625   mean click = 0.0625\n",
      "Batch 4525/15625   mean click = 0.109375\n",
      "Batch 4550/15625   mean click = 0.21875\n",
      "Batch 4575/15625   mean click = 0.140625\n",
      "Batch 4600/15625   mean click = 0.171875\n",
      "Batch 4625/15625   mean click = 0.15625\n",
      "Batch 4650/15625   mean click = 0.25\n",
      "Batch 4675/15625   mean click = 0.125\n",
      "Batch 4700/15625   mean click = 0.125\n",
      "Batch 4725/15625   mean click = 0.140625\n",
      "Batch 4750/15625   mean click = 0.109375\n",
      "Batch 4775/15625   mean click = 0.171875\n",
      "Batch 4800/15625   mean click = 0.171875\n",
      "Batch 4825/15625   mean click = 0.140625\n",
      "Batch 4850/15625   mean click = 0.1875\n",
      "Batch 4875/15625   mean click = 0.15625\n",
      "Batch 4900/15625   mean click = 0.1875\n",
      "Batch 4925/15625   mean click = 0.140625\n",
      "Batch 4950/15625   mean click = 0.1875\n",
      "Batch 4975/15625   mean click = 0.15625\n",
      "Batch 5000/15625   mean click = 0.140625\n",
      "Batch 5025/15625   mean click = 0.15625\n",
      "Batch 5050/15625   mean click = 0.15625\n",
      "Batch 5075/15625   mean click = 0.234375\n",
      "Batch 5100/15625   mean click = 0.1875\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Batch 5125/15625   mean click = 0.109375\n",
      "Batch 5150/15625   mean click = 0.171875\n",
      "Batch 5175/15625   mean click = 0.109375\n",
      "Batch 5200/15625   mean click = 0.171875\n",
      "Batch 5225/15625   mean click = 0.125\n",
      "Batch 5250/15625   mean click = 0.15625\n",
      "Batch 5275/15625   mean click = 0.203125\n",
      "Batch 5300/15625   mean click = 0.15625\n",
      "Batch 5325/15625   mean click = 0.140625\n",
      "Batch 5350/15625   mean click = 0.15625\n",
      "Batch 5375/15625   mean click = 0.203125\n",
      "Batch 5400/15625   mean click = 0.1875\n",
      "Batch 5425/15625   mean click = 0.109375\n",
      "Batch 5450/15625   mean click = 0.21875\n",
      "Batch 5475/15625   mean click = 0.140625\n",
      "Batch 5500/15625   mean click = 0.125\n",
      "Batch 5525/15625   mean click = 0.09375\n",
      "Batch 5550/15625   mean click = 0.109375\n",
      "Batch 5575/15625   mean click = 0.15625\n",
      "Batch 5600/15625   mean click = 0.109375\n",
      "Batch 5625/15625   mean click = 0.28125\n",
      "Batch 5650/15625   mean click = 0.109375\n",
      "Batch 5675/15625   mean click = 0.171875\n",
      "Batch 5700/15625   mean click = 0.125\n",
      "Batch 5725/15625   mean click = 0.03125\n",
      "Batch 5750/15625   mean click = 0.15625\n",
      "Batch 5775/15625   mean click = 0.15625\n",
      "Batch 5800/15625   mean click = 0.234375\n",
      "Batch 5825/15625   mean click = 0.171875\n",
      "Batch 5850/15625   mean click = 0.046875\n",
      "Batch 5875/15625   mean click = 0.140625\n",
      "Batch 5900/15625   mean click = 0.125\n",
      "Batch 5925/15625   mean click = 0.125\n",
      "Batch 5950/15625   mean click = 0.109375\n",
      "Batch 5975/15625   mean click = 0.15625\n",
      "Batch 6000/15625   mean click = 0.265625\n",
      "Batch 6025/15625   mean click = 0.140625\n",
      "Batch 6050/15625   mean click = 0.1875\n",
      "Batch 6075/15625   mean click = 0.109375\n",
      "Batch 6100/15625   mean click = 0.109375\n",
      "Batch 6125/15625   mean click = 0.109375\n",
      "Batch 6150/15625   mean click = 0.171875\n",
      "Batch 6175/15625   mean click = 0.1875\n",
      "Batch 6200/15625   mean click = 0.171875\n",
      "Batch 6225/15625   mean click = 0.265625\n",
      "Batch 6250/15625   mean click = 0.1875\n",
      "Batch 6275/15625   mean click = 0.140625\n",
      "Batch 6300/15625   mean click = 0.15625\n",
      "Batch 6325/15625   mean click = 0.203125\n",
      "Batch 6350/15625   mean click = 0.171875\n",
      "Batch 6375/15625   mean click = 0.109375\n",
      "Batch 6400/15625   mean click = 0.171875\n",
      "Batch 6425/15625   mean click = 0.171875\n",
      "Batch 6450/15625   mean click = 0.078125\n",
      "Batch 6475/15625   mean click = 0.125\n",
      "Batch 6500/15625   mean click = 0.203125\n",
      "Batch 6525/15625   mean click = 0.140625\n",
      "Batch 6550/15625   mean click = 0.234375\n",
      "Batch 6575/15625   mean click = 0.171875\n",
      "Batch 6600/15625   mean click = 0.21875\n",
      "Batch 6625/15625   mean click = 0.15625\n",
      "Batch 6650/15625   mean click = 0.109375\n",
      "Batch 6675/15625   mean click = 0.109375\n",
      "Batch 6700/15625   mean click = 0.09375\n",
      "Batch 6725/15625   mean click = 0.15625\n",
      "Batch 6750/15625   mean click = 0.109375\n",
      "Batch 6775/15625   mean click = 0.203125\n",
      "Batch 6800/15625   mean click = 0.15625\n",
      "Batch 6825/15625   mean click = 0.0625\n",
      "Batch 6850/15625   mean click = 0.09375\n",
      "Batch 6875/15625   mean click = 0.15625\n",
      "Batch 6900/15625   mean click = 0.125\n",
      "Batch 6925/15625   mean click = 0.1875\n",
      "Batch 6950/15625   mean click = 0.171875\n",
      "Batch 6975/15625   mean click = 0.15625\n",
      "Batch 7000/15625   mean click = 0.1875\n",
      "Batch 7025/15625   mean click = 0.140625\n",
      "Batch 7050/15625   mean click = 0.125\n",
      "Batch 7075/15625   mean click = 0.203125\n",
      "Batch 7100/15625   mean click = 0.171875\n",
      "Batch 7125/15625   mean click = 0.125\n",
      "Batch 7150/15625   mean click = 0.140625\n",
      "Batch 7175/15625   mean click = 0.15625\n",
      "Batch 7200/15625   mean click = 0.171875\n",
      "Batch 7225/15625   mean click = 0.109375\n",
      "Batch 7250/15625   mean click = 0.125\n",
      "Batch 7275/15625   mean click = 0.203125\n",
      "Batch 7300/15625   mean click = 0.140625\n",
      "Batch 7325/15625   mean click = 0.234375\n",
      "Batch 7350/15625   mean click = 0.1875\n",
      "Batch 7375/15625   mean click = 0.140625\n",
      "Batch 7400/15625   mean click = 0.15625\n",
      "Batch 7425/15625   mean click = 0.125\n",
      "Batch 7450/15625   mean click = 0.203125\n",
      "Batch 7475/15625   mean click = 0.109375\n",
      "Batch 7500/15625   mean click = 0.21875\n",
      "Batch 7525/15625   mean click = 0.109375\n",
      "Batch 7550/15625   mean click = 0.125\n",
      "Batch 7575/15625   mean click = 0.265625\n",
      "Batch 7600/15625   mean click = 0.15625\n",
      "Batch 7625/15625   mean click = 0.125\n",
      "Batch 7650/15625   mean click = 0.1875\n",
      "Batch 7675/15625   mean click = 0.203125\n",
      "Batch 7700/15625   mean click = 0.21875\n",
      "Batch 7725/15625   mean click = 0.140625\n",
      "Batch 7750/15625   mean click = 0.140625\n",
      "Batch 7775/15625   mean click = 0.140625\n",
      "Batch 7800/15625   mean click = 0.09375\n",
      "Batch 7825/15625   mean click = 0.140625\n",
      "Batch 7850/15625   mean click = 0.140625\n",
      "Batch 7875/15625   mean click = 0.21875\n",
      "Batch 7900/15625   mean click = 0.140625\n",
      "Batch 7925/15625   mean click = 0.140625\n",
      "Batch 7950/15625   mean click = 0.15625\n",
      "Batch 7975/15625   mean click = 0.1875\n",
      "Batch 8000/15625   mean click = 0.15625\n",
      "Batch 8025/15625   mean click = 0.203125\n",
      "Batch 8050/15625   mean click = 0.1875\n",
      "Batch 8075/15625   mean click = 0.15625\n",
      "Batch 8100/15625   mean click = 0.09375\n",
      "Batch 8125/15625   mean click = 0.203125\n",
      "Batch 8150/15625   mean click = 0.078125\n",
      "Batch 8175/15625   mean click = 0.15625\n",
      "Batch 8200/15625   mean click = 0.109375\n",
      "Batch 8225/15625   mean click = 0.171875\n",
      "Batch 8250/15625   mean click = 0.140625\n",
      "Batch 8275/15625   mean click = 0.125\n",
      "Batch 8300/15625   mean click = 0.15625\n",
      "Batch 8325/15625   mean click = 0.078125\n",
      "Batch 8350/15625   mean click = 0.109375\n",
      "Batch 8375/15625   mean click = 0.1875\n",
      "Batch 8400/15625   mean click = 0.15625\n",
      "Batch 8425/15625   mean click = 0.09375\n",
      "Batch 8450/15625   mean click = 0.046875\n",
      "Batch 8475/15625   mean click = 0.078125\n",
      "Batch 8500/15625   mean click = 0.1875\n",
      "Batch 8525/15625   mean click = 0.15625\n",
      "Batch 8550/15625   mean click = 0.046875\n",
      "Batch 8575/15625   mean click = 0.109375\n",
      "Batch 8600/15625   mean click = 0.140625\n",
      "Batch 8625/15625   mean click = 0.234375\n",
      "Batch 8650/15625   mean click = 0.1875\n",
      "Batch 8675/15625   mean click = 0.0625\n",
      "Batch 8700/15625   mean click = 0.09375\n",
      "Batch 8725/15625   mean click = 0.0625\n",
      "Batch 8750/15625   mean click = 0.09375\n",
      "Batch 8775/15625   mean click = 0.109375\n",
      "Batch 8800/15625   mean click = 0.21875\n",
      "Batch 8825/15625   mean click = 0.140625\n",
      "Batch 8850/15625   mean click = 0.078125\n",
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      "Batch 9000/15625   mean click = 0.203125\n",
      "Batch 9025/15625   mean click = 0.109375\n",
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      "Batch 9150/15625   mean click = 0.125\n",
      "Batch 9175/15625   mean click = 0.078125\n",
      "Batch 9200/15625   mean click = 0.171875\n",
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      "Batch 9250/15625   mean click = 0.171875\n",
      "Batch 9275/15625   mean click = 0.140625\n",
      "Batch 9300/15625   mean click = 0.203125\n",
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      "Batch 9375/15625   mean click = 0.140625\n",
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      "Batch 9450/15625   mean click = 0.15625\n",
      "Batch 9475/15625   mean click = 0.234375\n",
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      "Batch 9550/15625   mean click = 0.15625\n",
      "Batch 9575/15625   mean click = 0.125\n",
      "Batch 9600/15625   mean click = 0.203125\n",
      "Batch 9625/15625   mean click = 0.171875\n",
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      "Batch 10100/15625   mean click = 0.046875\n",
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      "Batch 10150/15625   mean click = 0.171875\n",
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      "Batch 10200/15625   mean click = 0.15625\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Batch 10225/15625   mean click = 0.125\n",
      "Batch 10250/15625   mean click = 0.140625\n",
      "Batch 10275/15625   mean click = 0.109375\n",
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      "Batch 10825/15625   mean click = 0.234375\n",
      "Batch 10850/15625   mean click = 0.21875\n",
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      "Batch 11050/15625   mean click = 0.140625\n",
      "Batch 11075/15625   mean click = 0.125\n",
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      "Batch 11150/15625   mean click = 0.1875\n",
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      "Batch 11400/15625   mean click = 0.1875\n",
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      "Batch 11450/15625   mean click = 0.171875\n",
      "Batch 11475/15625   mean click = 0.21875\n",
      "Batch 11500/15625   mean click = 0.125\n",
      "Batch 11525/15625   mean click = 0.1875\n",
      "Batch 11550/15625   mean click = 0.140625\n",
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      "Batch 11625/15625   mean click = 0.171875\n",
      "Batch 11650/15625   mean click = 0.234375\n",
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      "Batch 11700/15625   mean click = 0.1875\n",
      "Batch 11725/15625   mean click = 0.1875\n",
      "Batch 11750/15625   mean click = 0.140625\n",
      "Batch 11775/15625   mean click = 0.234375\n",
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      "Batch 12125/15625   mean click = 0.09375\n",
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      "Batch 12175/15625   mean click = 0.140625\n",
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      "Batch 12825/15625   mean click = 0.078125\n",
      "Batch 12850/15625   mean click = 0.125\n",
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      "Batch 12900/15625   mean click = 0.15625\n",
      "Batch 12925/15625   mean click = 0.125\n",
      "Batch 12950/15625   mean click = 0.0625\n",
      "Batch 12975/15625   mean click = 0.125\n",
      "Batch 13000/15625   mean click = 0.171875\n",
      "Batch 13025/15625   mean click = 0.125\n",
      "Batch 13050/15625   mean click = 0.09375\n",
      "Batch 13075/15625   mean click = 0.15625\n",
      "Batch 13100/15625   mean click = 0.171875\n",
      "Batch 13125/15625   mean click = 0.140625\n",
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      "Batch 13200/15625   mean click = 0.09375\n",
      "Batch 13225/15625   mean click = 0.125\n",
      "Batch 13250/15625   mean click = 0.21875\n",
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      "Batch 13300/15625   mean click = 0.078125\n",
      "Batch 13325/15625   mean click = 0.109375\n",
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      "Batch 13375/15625   mean click = 0.140625\n",
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      "Batch 13425/15625   mean click = 0.15625\n",
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      "Batch 13525/15625   mean click = 0.078125\n",
      "Batch 13550/15625   mean click = 0.109375\n",
      "Batch 13575/15625   mean click = 0.109375\n",
      "Batch 13600/15625   mean click = 0.15625\n",
      "Batch 13625/15625   mean click = 0.109375\n",
      "Batch 13650/15625   mean click = 0.140625\n",
      "Batch 13675/15625   mean click = 0.125\n",
      "Batch 13700/15625   mean click = 0.203125\n",
      "Batch 13725/15625   mean click = 0.09375\n",
      "Batch 13750/15625   mean click = 0.171875\n",
      "Batch 13775/15625   mean click = 0.1875\n",
      "Batch 13800/15625   mean click = 0.125\n",
      "Batch 13825/15625   mean click = 0.234375\n",
      "Batch 13850/15625   mean click = 0.140625\n",
      "Batch 13875/15625   mean click = 0.140625\n",
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      "Batch 14000/15625   mean click = 0.15625\n",
      "Batch 14025/15625   mean click = 0.125\n",
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      "Batch 14125/15625   mean click = 0.171875\n",
      "Batch 14150/15625   mean click = 0.15625\n",
      "Batch 14175/15625   mean click = 0.171875\n",
      "Batch 14200/15625   mean click = 0.21875\n",
      "Batch 14225/15625   mean click = 0.171875\n",
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      "Batch 14450/15625   mean click = 0.171875\n",
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      "Batch 14825/15625   mean click = 0.109375\n",
      "Batch 14850/15625   mean click = 0.203125\n",
      "Batch 14875/15625   mean click = 0.15625\n",
      "Batch 14900/15625   mean click = 0.09375\n",
      "Batch 14925/15625   mean click = 0.15625\n",
      "Batch 14950/15625   mean click = 0.171875\n",
      "Batch 14975/15625   mean click = 0.109375\n",
      "Batch 15000/15625   mean click = 0.09375\n",
      "Batch 15025/15625   mean click = 0.140625\n",
      "Batch 15050/15625   mean click = 0.203125\n",
      "Batch 15075/15625   mean click = 0.171875\n",
      "Batch 15100/15625   mean click = 0.15625\n",
      "Batch 15125/15625   mean click = 0.109375\n",
      "Batch 15150/15625   mean click = 0.125\n",
      "Batch 15175/15625   mean click = 0.171875\n",
      "Batch 15200/15625   mean click = 0.046875\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Batch 15225/15625   mean click = 0.109375\n",
      "Batch 15250/15625   mean click = 0.125\n",
      "Batch 15275/15625   mean click = 0.140625\n",
      "Batch 15300/15625   mean click = 0.125\n",
      "Batch 15325/15625   mean click = 0.109375\n",
      "Batch 15350/15625   mean click = 0.1875\n",
      "Batch 15375/15625   mean click = 0.125\n",
      "Batch 15400/15625   mean click = 0.15625\n",
      "Batch 15425/15625   mean click = 0.109375\n",
      "Batch 15450/15625   mean click = 0.140625\n",
      "Batch 15475/15625   mean click = 0.09375\n",
      "Batch 15500/15625   mean click = 0.25\n",
      "Batch 15525/15625   mean click = 0.203125\n",
      "Batch 15550/15625   mean click = 0.140625\n",
      "Batch 15575/15625   mean click = 0.171875\n",
      "Batch 15600/15625   mean click = 0.09375\n"
     ]
    }
   ],
   "source": [
    "pred_lst = predict_test(ctr_net, 64)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.151569"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(pred_lst)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 总结"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "以上就是点击率预估的完整过程，没有进行完整数据的训练，并且有很多超参可以调整，从只跑了一次epoch的结果来看，验证集上的LogLoss是0.468（全数据训练）~0.56（下采样训练），其他数据都在70%~80%之间，这跟FFM、GBDT和FM网络训练的准确率差不多。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从两个网络的训练结果上看，全数据训练的网络更倾向于预测成0，因为全数据存在严重的数据不均衡，采用下采样的数据训练方式能够改善网络的训练效果。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 扩展阅读"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " - [`Code for the 3rd place finish for Avazu Click-Through Rate Prediction`](https://github.com/infinitezxc/kaggle-avazu)\n",
    " - [`Kaggle ： Display Advertising Challenge( ctr 预估 )`](http://blog.csdn.net/hero_fantao/article/details/42747281)\n",
    " - [`用机器学习对CTR预估建模`](http://blog.csdn.net/JR_lu/article/details/54836968)\n",
    " - [`Beginner's Guide to Click-Through Rate Prediction with Logistic Regression`](https://turi.com/learn/gallery/notebooks/click_through_rate_prediction_intro.html)\n",
    " - [`2nd place solution for Avazu click-through rate prediction competition`](https://github.com/owenzhang/kaggle-avazu)\n",
    " - [`常见计算广告点击率预估算法总结`](https://zhuanlan.zhihu.com/p/29053940?group_id=916424345212342272)\n",
    " - [`3 Idiots' Approach for Display Advertising Challenge`](https://github.com/guestwalk/kaggle-2014-criteo)\n",
    " - [`Solution to the Outbrain Click Prediction competition`](https://github.com/alexeygrigorev/outbrain-click-prediction-kaggle)\n",
    " - [`Deep Interest Network for Click-Through Rate Prediction`](https://arxiv.org/abs/1706.06978)\n",
    " - [`Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction`](https://arxiv.org/abs/1704.05194)\n",
    " - [`重磅！阿里妈妈首次公开自研CTR预估核心算法MLR`](https://mp.weixin.qq.com/s/MtnHYmPVoDAid9SNHnlzUw)\n",
    " - [`阿里盖坤团队提出深度兴趣网络，更懂用户什么时候会剁手`](http://www.sohu.com/a/152084716_114877)\n",
    " - [`深入FFM原理与实践`](https://tech.meituan.com/deep-understanding-of-ffm-principles-and-practices.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 今天的分享就到这里，就酱~"
   ]
  }
 ],
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