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jittor.nn.Conv3d 没有对输入的维度进行检查,导致底层崩溃,也没有提供正确的引导信息
--------------------------------------------------------------------------- RuntimeError Traceback (most recent call last) Cell In[10], line 34 32 y = m(x) 33 return list(y.shape) ---> 34 go() Cell In[10], line 32, in go() 30 x = jittor.randn([1, 1, 28, 28]) 31 m = lenet() ---> 32 y = m(x) 33 return list(y.shape) File ~/miniconda3/envs/myconda/lib/python3.9/site-packages/jittor/__init__.py:1168, in Module.__call__(self, *args, **kw) 1167 def __call__(self, *args, **kw): -> 1168 return self.execute(*args, **kw) Cell In[10], line 22, in lenet.execute(self, x) 20 x = self.relu1(x) 21 x = self.pool1(x) ---> 22 x = self.conv2(x) 23 return x File ~/miniconda3/envs/myconda/lib/python3.9/site-packages/jittor/__init__.py:1168, in Module.__call__(self, *args, **kw) 1167 def __call__(self, *args, **kw): -> 1168 return self.execute(*args, **kw) File ~/miniconda3/envs/myconda/lib/python3.9/site-packages/jittor/nn.py:1138, in Conv3d.execute(self, x) 1137 def execute(self, x): -> 1138 return conv3d(x, self.weight, self.bias, self.stride, self.padding, self.dilation, self.groups) File ~/miniconda3/envs/myconda/lib/python3.9/site-packages/jittor/nn.py:1277, in conv3d(x, weight, bias, stride, padding, dilation, groups) 1274 out_channels = weight.shape[0] 1276 if jt.flags.use_cuda and jt.cudnn: -> 1277 y = jt.cudnn.ops.cudnn_conv3d(x, weight, *stride, *padding, *dilation, groups) 1278 elif groups == 1: 1279 N,C,D,H,W = x.shape RuntimeError: Wrong inputs arguments, Please refer to examples(help(jt.cudnn_conv3d)). Types of your inputs are: self = module, args = (Var, Var, int, int, int, int, int, int, int, int, int, int, ), The function declarations are: VarHolder* cudnn_conv3d(VarHolder* x, VarHolder* w, int strided, int strideh, int stridew, int paddingd, int paddingh, int paddingw, int dilationd=1, int dilationh=1, int dilationw=1, int groups=1, string xformat="ncdhw") Failed reason:[f 0906 09:47:16.870443 64 cudnn_conv3d_op.cc:37] Check failed x->shape.size()(4) == 5(5) Something wrong ... Could you please report this issue?
import os os.environ["disable_lock"] = "1" import jittor import jittor.nn as nn import jittor.optim as optim import numpy as np import copy class lenet(nn.Module): def __init__(self): super().__init__() self.conv1 = jittor.nn.Conv(in_channels=1, out_channels=6, kernel_size=5) self.relu1 = jittor.nn.ReLU() self.pool1 = jittor.nn.MaxPool2d(kernel_size=2, stride=2) self.conv2 = jittor.nn.Conv3d(in_channels=6, kernel_size=5, out_channels=16, dilation=(2, 7, 0)) def execute(self, x): x = self.conv1(x) x = self.relu1(x) x = self.pool1(x) x = self.conv2(x) return x def go(): jittor.flags.use_cuda = 1 x = jittor.randn([1, 1, 28, 28]) m = lenet() y = m(x) return list(y.shape) go()
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Describe the bug
jittor.nn.Conv3d 没有对输入的维度进行检查,导致底层崩溃,也没有提供正确的引导信息
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The text was updated successfully, but these errors were encountered: