From 0a9ee0a6b70681e97a00bd96899bd6b017a32c7a Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:03:30 +0800
Subject: [PATCH 01/95] Add finished status when find exp is not alive but not
 labeled

---
 src/lumo/exp/watch.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index e2dc867..e1203fc 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -228,6 +228,12 @@ def progress(self, is_alive=True):
                     exp = Experiment.from_disk(test_root)
                     if exp.is_alive == is_alive:
                         res.append(exp.dict())
+                    if not exp.is_alive and exp.properties['progress'].get('finished', None) is None:
+                        exp.dump_info('progress',
+                                      {
+                                          'end': strftime(), 'finished': True, 'end_code': -1,
+                                          'msg': 'ended by watcher'}
+                                      )
                 except:
                     continue
         return pd.DataFrame(res)

From 77166853e7a42f635ccad1b2574cbb8d690fe806 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:03:42 +0800
Subject: [PATCH 02/95] Metric

---
 src/lumo/exp/metric.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/src/lumo/exp/metric.py b/src/lumo/exp/metric.py
index abf5f61..641d7fa 100644
--- a/src/lumo/exp/metric.py
+++ b/src/lumo/exp/metric.py
@@ -45,14 +45,16 @@ def dump_metric(self, key, value, cmp: str, flush=True, **kwargs):
             dic[key] = value
             for kk, vv in kwargs.items():
                 dic[kk] = vv
+        else:
+            value = older
 
         if flush:
             self.flush()
         return value
 
     def dump_metrics(self, dic: dict, cmp: str):
-        for k, v in dic.items():
-            self.dump_metric(k, v, cmp)
+        return {k: self.dump_metric(k, v, cmp)
+                for k, v in dic.items()}
 
     def flush(self):
         """Writes the value of the row to a file."""

From 4213793526b917ffd6cd5c13df450df32343c6b5 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:03:59 +0800
Subject: [PATCH 03/95] End status content

---
 src/lumo/exp/experiment.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lumo/exp/experiment.py b/src/lumo/exp/experiment.py
index 358e9c3..d9f5392 100644
--- a/src/lumo/exp/experiment.py
+++ b/src/lumo/exp/experiment.py
@@ -679,7 +679,7 @@ def end(self, end_code=0, *args, **extra):
         if end_code == 0:
             self.dump_progress(1)
 
-        self.dump_info('progress', {'end': strftime(), 'finished': end_code == 0}, append=True)
+        self.dump_info('progress', {'end': strftime(), 'finished': True, 'end_code': end_code}, append=True)
         for hook in self._hooks.values():  # type: BaseExpHook
             hook.on_end(self, end_code=end_code, *args, **extra)
         return self

From c516ee7dfda0be278e57fe961e55f6d52d383041 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:04:05 +0800
Subject: [PATCH 04/95] Add test for metric

---
 tests/exp/test_metric.py | 49 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 49 insertions(+)
 create mode 100644 tests/exp/test_metric.py

diff --git a/tests/exp/test_metric.py b/tests/exp/test_metric.py
new file mode 100644
index 0000000..ca42c54
--- /dev/null
+++ b/tests/exp/test_metric.py
@@ -0,0 +1,49 @@
+import os
+import pytest
+import tempfile
+
+from lumo.exp.metric import Metric
+
+
+@pytest.fixture
+def metric():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        metric_fn = os.path.join(tmpdir, "test_metric.pkl")
+        yield Metric(metric_fn)
+
+
+def test_value(metric):
+    assert isinstance(metric.value, dict)
+
+
+def test_dump_metric_max(metric):
+    key = "test_key_max"
+    values = [2, 4, 1, 7, 5]
+    expected_value = max(values)
+    cur = values[0]
+    for value in values:
+        max_val = metric.dump_metric(key, value, "max")
+        cur = max(value, cur)
+        assert max_val == cur
+
+    assert metric.value[key] == expected_value
+
+
+def test_dump_metric(metric):
+    key = "test_key"
+    value = 10
+    metric.dump_metric(key, value, "max")
+    assert metric.value[key] == value
+
+
+def test_dump_metrics(metric):
+    dic = {"key1": 1, "key2": 2, "key3": 3}
+    cmp = "min"
+    result = metric.dump_metrics(dic, cmp)
+    assert result == {"key1": 1, "key2": 2, "key3": 3}
+
+
+def test_flush(metric):
+    metric.flush()
+    assert os.path.exists(metric.fn)
+    os.remove(metric.fn)

From cc14d85e3cf748d58e8bcb55430e81684211d0a8 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:28:22 +0800
Subject: [PATCH 05/95] Add deprecated warning

---
 src/lumo/analyse/__init__.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/src/lumo/analyse/__init__.py b/src/lumo/analyse/__init__.py
index 7eeb38a..0af59d3 100644
--- a/src/lumo/analyse/__init__.py
+++ b/src/lumo/analyse/__init__.py
@@ -1,2 +1,5 @@
+import warnings
+
 from .collect import collect_table_rows, flatten_dict, flatten_params, flatten_metric
 from .condition import C, filter_by_condition
+warnings.warn("lumo.analyse has been deprecated and will be removed soon, please use lumo.exp.Watcher instead.")
\ No newline at end of file

From 3ddc382a5eda4139c4e22d760574e18029a06180 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:28:34 +0800
Subject: [PATCH 06/95] Add notes, fix no return problem

---
 src/lumo/exp/experiment.py | 46 ++++++++++++++++++++++++++++++++++++--
 1 file changed, 44 insertions(+), 2 deletions(-)

diff --git a/src/lumo/exp/experiment.py b/src/lumo/exp/experiment.py
index d9f5392..f54b1ce 100644
--- a/src/lumo/exp/experiment.py
+++ b/src/lumo/exp/experiment.py
@@ -367,12 +367,24 @@ def exec_argv(self):
             return []
 
     def _trigger_change(self, func):
-        #  test_root update some files
+        """
+        Decorator function that updates the heartbeat file before executing the decorated function.
+
+        The heartbeat file indicates that a change has occurred in the experiment directory.
+
+        Args:
+            func: the function to be decorated.
+
+        Returns:
+            A decorated function.
+        """
+
+        # test_root update some files
         @wraps(func)
         def inner(*args, **kwargs):
             fn = self.heartbeat_fn
             io.dump_text(self.info_dir, fn)
-            func(*args, **kwargs)
+            return func(*args, **kwargs)
 
         return inner
 
@@ -479,15 +491,39 @@ def load_info(self, key: str):
             return {}
 
     def load_note(self):
+        """
+        Loads the contents of the note file, if it exists.
+
+        Returns:
+            A string representing the contents of the note file, or an empty string if the file does not exist.
+        """
         fn = self.mk_ipath('note.md')
         if os.path.exists(fn):
             return io.load_text(fn)
         return ''
 
     def dump_tags(self, *tags):
+        """
+        Dumps the experiment's tags to the info file.
+
+        Args:
+            *tags: a variable-length argument list of tags to be added to the experiment.
+
+        Returns:
+            None.
+        """
         self.dump_info('tags', tags)
 
     def dump_note(self, note: str):
+        """
+        Dumps the contents of the note to the note file.
+
+        Args:
+            note: a string representing the contents of the note.
+
+        Returns:
+            None.
+        """
         fn = self.mk_ipath('note.md')
         self.set_prop('note', note)
         io.dump_text(note, fn)
@@ -521,9 +557,15 @@ def load_string(self, key: str):
         return io.load_text(fn)
 
     def dump_metric(self, key, value, cmp: str, flush=True, **kwargs):
+        """
+        See Metric for details.
+        """
         return self.metric.dump_metric(key, value, cmp, flush, **kwargs)
 
     def dump_metrics(self, dic: dict, cmp: str):
+        """
+        See Metric for details.
+        """
         return self.metric.dump_metrics(dic, cmp)
 
     @property

From 91f201162f135304868051d53d08aec57f98abd4 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:28:40 +0800
Subject: [PATCH 07/95] Add docstring

---
 src/lumo/exp/metric.py | 65 ++++++++++++++++++++++++++++++++++++++----
 1 file changed, 60 insertions(+), 5 deletions(-)

diff --git a/src/lumo/exp/metric.py b/src/lumo/exp/metric.py
index 641d7fa..e7e9fdd 100644
--- a/src/lumo/exp/metric.py
+++ b/src/lumo/exp/metric.py
@@ -4,9 +4,26 @@
 
 class Metric:
     """
+    A class that handles metric values and saving/loading them to/from disk.
+
+    Attributes:
+        fn (str): The file path of the metric file.
+        _metric (dict): A dictionary containing the metric values.
+        persistent (bool): A boolean value indicating whether to save the metric values to disk.
     """
 
     def __init__(self, metric_fn, persistent=True):
+        """
+        Initializes a new instance of the Metric class.
+
+        Args:
+            metric_fn (str): The file path of the metric file.
+            persistent (bool): A boolean value indicating whether to save the metric values to disk.
+                Default is True.
+
+        Returns:
+            None.
+        """
         os.makedirs(os.path.dirname(os.path.abspath(metric_fn)), exist_ok=True)
         self.fn = metric_fn
         self._metric = {}
@@ -17,14 +34,35 @@ def __init__(self, metric_fn, persistent=True):
     @property
     def value(self):
         """
-        A property that returns the metric values of the row.
+        A property that returns the metric values.
 
         Returns:
-            dict: A dictionary containing the metric values of the row.
+            dict: A dictionary containing the metric values.
         """
         return self._metric
 
     def dump_metric(self, key, value, cmp: str, flush=True, **kwargs):
+        """
+        Updates the metric value for a given key.
+
+        If the metric value for the given key is not set or the new value is better than the
+        existing value based on the comparison type specified by cmp, the metric value is updated
+        with the new value. The function returns the updated value.
+
+        Args:
+            key (str): The key for the metric value.
+            value (float): The new metric value.
+            cmp (str): The type of comparison to use when updating the metric value. Must be 'max' or 'min'.
+            flush (bool): A boolean value indicating whether to save the updated metric values to disk.
+                Default is True.
+            **kwargs: Additional key-value pairs to store with the metric value.
+
+        Returns:
+            float: The updated metric value.
+
+        Raises:
+            NotImplementedError: If cmp is not 'max' or 'min'.
+        """
         dic = self.value
         older = dic.setdefault(key, None)
 
@@ -53,10 +91,27 @@ def dump_metric(self, key, value, cmp: str, flush=True, **kwargs):
         return value
 
     def dump_metrics(self, dic: dict, cmp: str):
-        return {k: self.dump_metric(k, v, cmp)
-                for k, v in dic.items()}
+        """
+        Updates multiple metric values with a dictionary.
+
+        The function calls dump_metric for each key-value pair in the input dictionary and returns
+        a dictionary containing the updated metric values.
+
+        Args:
+            dic (dict): A dictionary containing the key-value pairs to update.
+            cmp (str): The type of comparison to use when updating the metric values. Must be 'max' or 'min'.
+
+        Returns:
+            dict: A dictionary containing the updated metric values.
+        """
+        res = {k: self.dump_metric(k, v, cmp, flush=False)
+               for k, v in dic.items()}
+        self.flush()
+        return res
 
     def flush(self):
-        """Writes the value of the row to a file."""
+        """
+        Writes the metric values to a file.
+        """
         if self.persistent:
             IO.dump_pkl(self.value, self.fn)

From e0357bb1797a06585946250bd582d3108675d664 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:28:44 +0800
Subject: [PATCH 08/95] Add docstring

---
 src/lumo/proc/path.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/lumo/proc/path.py b/src/lumo/proc/path.py
index 8cff01b..55547ba 100644
--- a/src/lumo/proc/path.py
+++ b/src/lumo/proc/path.py
@@ -112,6 +112,7 @@ def metricroot():
 
 
 def dbroot():
+    """Root path to store experiment information. Default is `~/.lumo/database`"""
     DB_ROOT = glob.get('db_root', None)
     if DB_ROOT:
         res = DB_ROOT

From 20d3653efc4d018499fa4bb986205c9f747d7ee8 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:28:50 +0800
Subject: [PATCH 09/95] Add docstring

---
 src/lumo/trainer/trainer.py | 35 +++++++++++++++++++++++++++++++++++
 1 file changed, 35 insertions(+)

diff --git a/src/lumo/trainer/trainer.py b/src/lumo/trainer/trainer.py
index 27338f9..93b700d 100644
--- a/src/lumo/trainer/trainer.py
+++ b/src/lumo/trainer/trainer.py
@@ -1012,28 +1012,63 @@ def wait_for_everyone(self):
         self.accelerate.wait_for_everyone()
 
     def save_best_model(self):
+        """
+        Saves the best model checkpoint and metadata.
+
+        If the current process is the main process, saves the best model checkpoint as 'best_model.ckpt'
+        and its metadata as 'best_model.json'. If not, saves the checkpoint and metadata with the process rank
+        appended to the filename, e.g., 'best_model-<rank>.ckpt' and 'best_model-<rank>.json'.
+
+        The saved metadata includes the global training steps and the value of the experiment's best metric.
+
+        Args:
+            self: the Experiment object.
+
+        Returns:
+            None.
+        """
         if self.is_main:
             file = self.exp.mk_bpath('models', 'best_model.ckpt')
             file_info = self.exp.mk_bpath('models', 'best_model.json')
         else:
             file = self.exp.mk_bpath('models', f'best_model-{self.local_rank}.ckpt')
             file_info = self.exp.mk_bpath('models', f'best_model-{self.local_rank}.json')
+
         torch.save(self.state_dict(), file)
 
         with open(file_info, 'w') as w:
             w.write(json.dumps({'global_steps': self.global_steps, 'metric': self.exp.metric.value}))
+
         self.logger.info(f'saved best model at {file}')
         self.wait_for_everyone()
 
     def save_last_model(self):
+        """
+        Saves the last model checkpoint and metadata.
+
+        If the current process is the main process, saves the last model checkpoint as 'last_model.ckpt'
+        and its metadata as 'last_model.json'. If not, saves the checkpoint and metadata with the process rank
+        appended to the filename, e.g., 'last_model-<rank>.ckpt' and 'last_model-<rank>.json'.
+
+        The saved metadata includes the global training steps and the value of the experiment's best metric.
+
+        Args:
+            self: the Experiment object.
+
+        Returns:
+            None.
+        """
         if self.is_main:
             file = self.exp.mk_bpath('models', 'last_model.ckpt')
             file_info = self.exp.mk_bpath('models', 'last_model.json')
         else:
             file = self.exp.mk_bpath('models', f'last_model-{self.local_rank}.ckpt')
             file_info = self.exp.mk_bpath('models', f'last_model-{self.local_rank}.json')
+
         torch.save(self.state_dict(), file)
+
         with open(file_info, 'w') as w:
             w.write(json.dumps({'global_steps': self.global_steps, 'metric': self.exp.metric.value}))
+
         self.logger.info(f'saved last model at {file}')
         self.wait_for_everyone()

From 5224a5b421c044ded72409d5c46b81515ded4a48 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:28:55 +0800
Subject: [PATCH 10/95] Add docstring

---
 src/lumo/utils/subprocess.py | 11 +++++++++++
 1 file changed, 11 insertions(+)

diff --git a/src/lumo/utils/subprocess.py b/src/lumo/utils/subprocess.py
index 5ed5e9f..f1e073d 100644
--- a/src/lumo/utils/subprocess.py
+++ b/src/lumo/utils/subprocess.py
@@ -5,6 +5,17 @@
 
 
 def run_command(command, cwd=None, env=None):
+    """
+    Executes a command in the shell and captures its standard output and standard error.
+
+    Args:
+        command: a string representing the command to execute in the shell.
+        cwd: a string representing the working directory to execute the command in. Default is None.
+        env: a dictionary representing the environment variables to set for the command. Default is None.
+
+    Returns:
+        The return code of the executed command.
+    """
     proc = subprocess.Popen(command,
                             cwd=cwd,
                             env=env,

From 05123edd7d0dd4f92ceeda0f9eefd90fa2634087 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:29:48 +0800
Subject: [PATCH 11/95] Add docstring

---
 src/lumo/utils/fmt.py | 21 +++++++++++++++++++--
 1 file changed, 19 insertions(+), 2 deletions(-)

diff --git a/src/lumo/utils/fmt.py b/src/lumo/utils/fmt.py
index 7ba7897..ef6c537 100644
--- a/src/lumo/utils/fmt.py
+++ b/src/lumo/utils/fmt.py
@@ -72,7 +72,15 @@ def indent_print(text, indent='    '):
 
 
 def format_second(sec: int) -> str:
-    """Formats a duration given in seconds into a human-readable string."""
+    """
+    Formats a duration given in seconds into a human-readable string.
+
+    Args:
+        sec: the duration in seconds.
+
+    Returns:
+        A human-readable string representing the duration.
+    """
     sec, ms = divmod(sec, 1)
     if sec > 60:
         min, sec = divmod(sec, 60)
@@ -90,5 +98,14 @@ def format_second(sec: int) -> str:
     return fmt
 
 
-def format_timedelta(td: timedelta):
+def format_timedelta(td: timedelta) -> str:
+    """
+    Formats a timedelta object into a human-readable string.
+
+    Args:
+        td: a timedelta object.
+
+    Returns:
+        A human-readable string representing the timedelta.
+    """
     return format_second(td.total_seconds())

From 92058189089d3da321ab2203f6ad49a0bfd3fff2 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:37:28 +0800
Subject: [PATCH 12/95] Add docstring

---
 src/lumo/exp/experiment.py |  75 +++++++++++++-
 src/lumo/exp/watch.py      | 200 ++++++++++++-------------------------
 2 files changed, 136 insertions(+), 139 deletions(-)

diff --git a/src/lumo/exp/experiment.py b/src/lumo/exp/experiment.py
index f54b1ce..8d51146 100644
--- a/src/lumo/exp/experiment.py
+++ b/src/lumo/exp/experiment.py
@@ -382,6 +382,7 @@ def _trigger_change(self, func):
         # test_root update some files
         @wraps(func)
         def inner(*args, **kwargs):
+            """wrap function"""
             fn = self.heartbeat_fn
             io.dump_text(self.info_dir, fn)
             return func(*args, **kwargs)
@@ -616,7 +617,17 @@ def blob_dir(self):
         os.makedirs(d, exist_ok=True)
         return d
 
-    def _mk_path(self, *path: str, is_dir) -> str:
+    def _mk_path(self, *path: str, is_dir: bool) -> str:
+        """
+        Helper method to create a directory path if it does not exist and return the path.
+
+        Args:
+            *path: tuple of path strings to be joined.
+            is_dir: boolean flag indicating whether the path is a directory.
+
+        Returns:
+            str: the full path created.
+        """
         path = os.path.join(*path)
         if is_dir:
             os.makedirs(path, exist_ok=True)
@@ -624,16 +635,56 @@ def _mk_path(self, *path: str, is_dir) -> str:
             os.makedirs(os.path.dirname(path), exist_ok=True)
         return path
 
-    def mk_ipath(self, *path, is_dir=False):
+    def mk_ipath(self, *path: str, is_dir: bool = False) -> str:
+        """
+        Creates a directory path within the experiment's info directory.
+
+        Args:
+            *path: tuple of path strings to be joined.
+            is_dir: boolean flag indicating whether the path is a directory. Default is False.
+
+        Returns:
+            str: the full path created.
+        """
         return self._mk_path(self.info_dir, *path, is_dir=is_dir)
 
-    def mk_cpath(self, *path, is_dir=False):
+    def mk_cpath(self, *path: str, is_dir: bool = False) -> str:
+        """
+        Creates a directory path within the experiment's cache directory.
+
+        Args:
+            *path: tuple of path strings to be joined.
+            is_dir: boolean flag indicating whether the path is a directory. Default is False.
+
+        Returns:
+            str: the full path created.
+        """
         return self._mk_path(self.cache_dir, *path, is_dir=is_dir)
 
-    def mk_bpath(self, *path, is_dir=False):
+    def mk_bpath(self, *path: str, is_dir: bool = False) -> str:
+        """
+        Creates a directory path within the experiment's blob directory.
+
+        Args:
+            *path: tuple of path strings to be joined.
+            is_dir: boolean flag indicating whether the path is a directory. Default is False.
+
+        Returns:
+            str: the full path created.
+        """
         return self._mk_path(self.blob_dir, *path, is_dir=is_dir)
 
-    def mk_rpath(self, *path, is_dir=False):
+    def mk_rpath(self, *path: str, is_dir: bool = False) -> str:
+        """
+        Creates a directory path within the user's home directory.
+
+        Args:
+            *path: tuple of path strings to be joined.
+            is_dir: boolean flag indicating whether the path is a directory. Default is False.
+
+        Returns:
+            str: the full path created.
+        """
         return self._mk_path(libhome(), *path, is_dir=is_dir)
 
     @classmethod
@@ -765,6 +816,18 @@ def exp_func():
 
     @classmethod
     def from_cache(cls, dic: dict):
+        """
+        Creates an Experiment object from a cached dictionary.
+
+        The cached dictionary should have the same format as the one returned by the Experiment.to_cache() method.
+
+        Args:
+            cls: the Experiment class.
+            dic: a dictionary with the cached Experiment data.
+
+        Returns:
+            An Experiment object.
+        """
         paths = dic.pop('paths', {})
         _ = dic.pop('metrics')
         self = cls(exp_name=dic['exp_name'], test_name=dic['test_name'], paths=paths)
@@ -816,12 +879,14 @@ def from_disk(cls, path):
         return self
 
     def cache(self):
+        """Cache information of current test."""
         return {
             **self.properties,
             'metrics': self.metric.value,
         }
 
     def dict(self):
+        """Get full information of current test, including dynamic status."""
         return {
             **self.properties,
             'is_alive': self.is_alive,
diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index e1203fc..f7628cc 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -74,6 +74,8 @@ def not_in_(ser, value):
 
 
 class Condition:
+    """Represents a condition to filter data based on a certain criteria."""
+
     def __init__(self, name: str = None, value=None, op=None):
         self.name = name
         self.value = value
@@ -130,18 +132,43 @@ def __repr__(self):
         return f'C({self.name} {self.op} {self.value})'
 
     def in_(self, lis):
-        """condition of `in` operation"""
+        """
+        Sets the condition to evaluate if the value is in a given list.
+
+        Args:
+            lis (list): the list of values to compare against.
+
+        Returns:
+            The current instance of the Condition class with the comparison operator and value set.
+        """
         self.op = 'in'
         self.value = set(lis)
         return self
 
     def not_in_(self, lis):
-        """condition of `.duplicated(value) == False` operation"""
+        """
+        Sets the condition to evaluate if the value is not in a given list.
+
+        Args:
+            lis (list): the list of values to compare against.
+
+        Returns:
+            The current instance of the Condition class with the comparison operator and value set.
+        """
         self.op = 'notin'
         self.value = set(lis)
         return self
 
     def mask(self, df):
+        """
+        Returns a boolean mask of the given DataFrame based on the condition.
+
+        Args:
+            df (pd.DataFrame): the DataFrame to evaluate.
+
+        Returns:
+            A boolean mask of the given DataFrame based on the condition.
+        """
         names = self.name.split('.')
         value = df
         for i in names:
@@ -152,6 +179,7 @@ def mask(self, df):
         return mapping[self.op](value, self.value)
 
     def apply(self, df):
+        """Returns a new DataFrame with only the rows that meet the condition."""
         return df[self.mask(df)]
 
 
@@ -159,10 +187,14 @@ def apply(self, df):
 
 
 class Watcher:
-    """List and watch experiments with time order
+    """
+    A class for listing and watching experiments with time order and caching test information in 'metrics/<experiment>.sqlite'.
 
-    Cache test_information in
-    metrics/<experiment>.sqlite
+    Attributes:
+        exp_root (str): The root directory to search for experiments.
+        hb_root (str): The root directory to search for heartbeat files.
+        pid_root (str): The root directory to search for PID files.
+        db_root (str): The root directory to store the experiment databases.
     """
 
     def __init__(self, exp_root=None, hb_root=None, pid_root=None, db_root=None):
@@ -183,6 +215,12 @@ def __init__(self, exp_root=None, hb_root=None, pid_root=None, db_root=None):
         self.pid_root = pid_root
 
     def load(self):
+        """
+        Loads the experiment information from heartbeat files and the experiment databases.
+
+        Returns:
+            A pandas DataFrame containing the experiment information sorted by experiment name and test name.
+        """
         res = {}
         updates = {}
         if not os.path.exists(self.hb_root):
@@ -217,7 +255,15 @@ def load(self):
         return df.reset_index(drop=True)
 
     def progress(self, is_alive=True):
-        """return the alive process"""
+        """
+        Returns a DataFrame of alive experiments.
+
+        Args:
+            is_alive (bool): A boolean flag indicating whether to return only alive experiments.
+
+        Returns:
+            A pandas DataFrame containing the experiment information of alive experiments.
+        """
         res = []
         for root, dirs, fs in os.walk(self.pid_root):
             for f in fs:
@@ -264,6 +310,7 @@ def widget(self,
                params_filter: list = None,
                metric_filter: list = None
                ):
+        """Create a user interface in jupyter with ipywidget"""
         assert params_filter is None or isinstance(params_filter, list)
         assert metric_filter is None or isinstance(metric_filter, list)
 
@@ -271,12 +318,23 @@ def widget(self,
         from IPython.display import display
 
         def make_row(dic: dict):
+            """
+            Helper function for creating a row in the widgets grid.
+
+            Args:
+                dic (dict): The dictionary containing the experiment information.
+
+            Returns:
+                A list of ipywidgets objects for the row.
+            """
             exp = Experiment.from_cache(dic.copy())
 
             def on_note_update(sender):
+                """when note textarea update"""
                 exp.dump_note(sender['new'])
 
             def on_tag_update(sender):
+                """when tag component update"""
                 exp.dump_tags(*sender['new'])
 
             note_ui = widgets.Textarea(dic['note'])
@@ -319,6 +377,7 @@ def on_tag_update(sender):
         end_filter = widgets.DatetimePicker()
 
         def status_filter(sender):
+            """when filter condition changed"""
             print(sender)
             make()
 
@@ -332,6 +391,7 @@ def make(
                 start=widgets.DatetimePicker(),
                 end=widgets.DatetimePicker(),
         ):
+            """make widgets with filter condition."""
             if status == 'running':
                 df = self.progress()
             elif status == 'finished':
@@ -412,131 +472,3 @@ def make(
                 grid,
 
             )
-
-            # return display(
-            #     widgets.HTML(styles['row-radio']),
-            #     widgets.HTML("""
-            #     <style>
-            #     .widget-box, .jupyter-widget-box {border: 1px solid !important;}
-            #     </style>
-            # """),
-            #     grid, clear=True)
-
-
-class ExperimentWidget:
-    @overload
-    def __init__(self, exp_name, test_name,
-                 progress: dict,
-                 params: dict, metrics: dict, note: str, tags: set, exp: Experiment):
-        pass
-
-    def __init__(self, **kwargs):
-        from ipywidgets import widgets
-        self.wid = widgets
-        self.exp = kwargs.pop('exp')  # type: Experiment
-        self._prop = kwargs
-
-        self._widgets = {
-            'exp_name': widgets.HTML(self._prop['exp_name']),
-            'test_name': widgets.HTML(self._prop['test_name']),
-            'metrics': widgets.VBox(
-                [widgets.HTML(f'{k}: {v}') for k, v in self._prop['metrics'].items() if
-                 isinstance(v, numbers.Number)]),
-        }
-
-        self._params_widgets = {}
-
-        note_ui = widgets.Textarea(self._prop['note'])
-
-        note_ui.continuous_update = False
-        note_ui.observe(self.on_note_update, names='value', type='change')
-        self._widgets['note'] = note_ui
-
-        tag_ui = widgets.TagsInput(value=list(self._prop['tags']))
-        self._widgets['tags'] = tag_ui
-        tag_ui.observe(self.on_tag_update, names='value', type='change')
-
-    def on_note_update(self, sender):
-        self.exp.dump_note(sender['new'])
-
-    def on_tag_update(self, sender):
-        self.exp.dump_tags(*sender['new'])
-
-    def set_key_params(self, keys: list):
-        self._params_widgets.clear()
-        for key in keys:
-            self._params_widgets[key] = self.wid.HTML(
-                f"""<code><b>{key}</b>: {pformat(self._prop['params'][key], width=10, indent=2, compact=True)}</code>""")
-
-    def sep(self):
-        return self.wid.Output(layout={'border': '1px solid black'})
-
-    def id_flag(self):
-        return self.wid.VBox([
-            self._widgets['exp_name'],
-            self._widgets['test_name'],
-        ])
-
-    def key_params(self):
-        return self.wid.VBox([
-            *self._params_widgets.values()
-        ])
-
-    def editable(self):
-        return self.wid.VBox([
-            self._widgets['note'],
-            self.sep(),
-            self._widgets['tags'],
-        ])
-
-    def time(self):
-        now = datetime.now()
-        start = strptime(datestr=self._prop['progress']['start'])
-        end = strptime(datestr=self._prop['progress']['start'])
-        return self.wid.VBox([
-            self.wid.HTML(f"""Start at: {format_timedelta(now - start)}"""),
-            self.wid.HTML(f"""End at: {format_timedelta(now - end)}"""),
-        ])
-
-    def widget_dict(self):
-        return {
-            'id_flag': self.id_flag(),
-            'time': self.time(),
-            'editable': self.editable(),
-            'params': self.key_params(),
-        }
-
-    def widget(self):
-        params = self.key_params()
-        params = [
-            self.sep(),
-            params,
-        ]
-
-        hbox = self.wid.HBox([
-            self.id_flag(),
-            self.time(),
-            self._widgets['metrics'],
-            self.editable(),
-            self.key_params(),
-        ])
-
-        return hbox
-
-    @classmethod
-    def from_experiment(cls, exp: Experiment):
-        tags = exp.properties.get('tags', [])
-        try:
-            tags = set(tags)
-        except:
-            tags = set()
-        return cls(
-            exp_name=exp.exp_name,
-            test_name=exp.test_name,
-            progress=exp.properties.get('progress', {}),
-            params=exp['params'],
-            metrics=exp.metric.value,
-            note=exp.properties.get('note', ''),
-            tags=tags,
-            exp=exp,
-        )

From 33bb865c92e678d066c3e37adf46a6c649ef180e Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:48:37 +0800
Subject: [PATCH 13/95] Deprecated some code

---
 src/lumo/exp/experiment.py    |  4 +--
 src/lumo/exp/finder.py        | 29 +--------------
 src/lumo/exp/watch.py         | 68 +++++++++++++++++++++++++++++------
 src/lumo/sketch/vis/parser.py | 38 ++++++++++----------
 4 files changed, 80 insertions(+), 59 deletions(-)

diff --git a/src/lumo/exp/experiment.py b/src/lumo/exp/experiment.py
index 8d51146..f2b7999 100644
--- a/src/lumo/exp/experiment.py
+++ b/src/lumo/exp/experiment.py
@@ -123,7 +123,6 @@ def __init__(self, exp_name: str, test_name=None, paths=None):
         self.dump_note = self._trigger_change(self.dump_note)
         self.dump_info = self._trigger_change(self.dump_info)
 
-        self.add_exit_hook(self.end)
         self.logger = Logger()
 
     def __getitem__(self, item):
@@ -737,6 +736,7 @@ def initial(self):
         self.dump_progress(0)
         # register progress
         io.dump_text(self.info_dir, self.pid_fn)
+        self.add_exit_hook(self.end)
 
     @call_on_main_process_wrap
     def start(self):
@@ -848,7 +848,7 @@ def from_disk(cls, path):
         Raises:
             ValueError: If the path is not a valid test root directory.
         """
-        from .finder import is_test_root
+        from lumo.exp.watch import is_test_root
         if not is_test_root(path):
             raise ValueError(f'{path} is not a valid test_root')
         path = os.path.abspath(path)
diff --git a/src/lumo/exp/finder.py b/src/lumo/exp/finder.py
index 5398917..dec377f 100644
--- a/src/lumo/exp/finder.py
+++ b/src/lumo/exp/finder.py
@@ -11,9 +11,9 @@
 import os
 from typing import List, Dict, Any
 
+from lumo.exp.watch import is_test_root, is_test_name
 from lumo.proc.path import libhome, exproot, metricroot
 from lumo.utils.fmt import indent_print
-from lumo.utils import re
 
 from . import Experiment
 
@@ -112,33 +112,6 @@ def find_path_from_test_name(test_name: str) -> str:
     return None
 
 
-def is_test_name(test_name: str) -> bool:
-    """
-    Determines if the specified string is a valid test name.
-
-    Args:
-        test_name: The string to check.
-
-    Returns:
-        True if the string is a valid test name, False otherwise.
-    """
-    return re.search(r'^\d{6}\.\d{3}\.[a-z\d]{2}t$', test_name) is not None
-
-
-def is_test_root(path: str) -> bool:
-    """
-    Determines if the specified path is a valid test root.
-
-    Args:
-        path: The path to check.
-
-    Returns:
-        True if the path is a valid test root, False otherwise.
-    """
-    test_name = os.path.basename(path.rstrip('/'))
-    return is_test_name(test_name)
-
-
 def retrieval_test_root(test_flag: str) -> str:
     """
     Returns the test root directory for the specified test name or test root.
diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index f7628cc..06fa476 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -19,7 +19,9 @@
 
 """
 import numbers
+import os
 import os.path
+import re
 from typing import List, Dict, overload
 from pprint import pformat
 import pandas as pd
@@ -214,14 +216,11 @@ def __init__(self, exp_root=None, hb_root=None, pid_root=None, db_root=None):
         self.hb_root = hb_root
         self.pid_root = pid_root
 
-    def load(self):
-        """
-        Loads the experiment information from heartbeat files and the experiment databases.
+    def retrieve(self, test_name=None):
+        raise NotImplementedError()
 
-        Returns:
-            A pandas DataFrame containing the experiment information sorted by experiment name and test name.
-        """
-        res = {}
+    def update(self):
+        """Diff & Update"""
         updates = {}
         if not os.path.exists(self.hb_root):
             return pd.DataFrame()
@@ -242,13 +241,35 @@ def load(self):
 
         for exp_name, tests in updates.items():
             dic = PDict(os.path.join(self.db_root, f'{exp_name}.sqlite'))
-            for test_name, test_prop in dic.items():
-                res[test_name] = test_prop
 
             for test in tests:
                 dic[test['test_name']] = test
-                res[test['test_name']] = test
             dic.flush()
+        return updates
+
+    def load(self):
+        """
+        Loads the experiment information from heartbeat files and the experiment databases.
+
+        Returns:
+            A pandas DataFrame containing the experiment information sorted by experiment name and test name.
+        """
+        res = {}
+        updates = self.update()
+
+        for dic_fn in os.listdir(self.db_root):
+            if not dic_fn.endswith('sqlite'):
+                continue
+            dic = PDict(os.path.join(self.db_root, dic_fn))
+            exp_name = os.path.splitext(dic_fn)[0]
+
+            for test_name, test_prop in dic.items():
+                res[test_name] = test_prop
+
+            if exp_name in updates:
+                for test in updates[exp_name]:
+                    res[test['test_name']] = test
+                dic.flush()
 
         df = pd.DataFrame(res.values())
         df = df.sort_values(['exp_name', 'test_name'])
@@ -472,3 +493,30 @@ def make(
                 grid,
 
             )
+
+
+def is_test_root(path: str) -> bool:
+    """
+    Determines if the specified path is a valid test root.
+
+    Args:
+        path: The path to check.
+
+    Returns:
+        True if the path is a valid test root, False otherwise.
+    """
+    test_name = os.path.basename(path.rstrip('/'))
+    return is_test_name(test_name)
+
+
+def is_test_name(test_name: str) -> bool:
+    """
+    Determines if the specified string is a valid test name.
+
+    Args:
+        test_name: The string to check.
+
+    Returns:
+        True if the string is a valid test name, False otherwise.
+    """
+    return re.search(r'^\d{6}\.\d{3}\.[a-z\d]{2}t$', test_name) is not None
diff --git a/src/lumo/sketch/vis/parser.py b/src/lumo/sketch/vis/parser.py
index b1f9406..7d47aea 100644
--- a/src/lumo/sketch/vis/parser.py
+++ b/src/lumo/sketch/vis/parser.py
@@ -23,25 +23,25 @@ class Step:
     step: int
 
 
-def find_metric_fron_test_root(test_root):
-    test_root = finder.retrieval_test_root(test_root)
-    if test_root is None:
-        return False, {}
-
-    exp = Experiment.from_disk(test_root)
-    if exp.has_prop('tensorboard_args'):
-        tb = exp.properties.get('tensorboard_args')
-        metrics = parse_fron_tensorboard(tb['log_dir'])
-    elif exp.has_prop('logger_args'):
-        tb = exp.properties.get('logger_args')
-        metrics = parse_from_log(tb['log_dir'])
-    else:
-        fs = [i for i in os.listdir(exp.test_root)]
-        if len([f for f in fs if f.endswith('.log')]) > 0:
-            metrics = parse_from_log(os.path.join(exp.test_root, fs[0]))
-        else:
-            metrics = {}
-    return True, metrics
+# def find_metric_fron_test_root(test_root):
+#     test_root = finder.retrieval_test_root(test_root)
+#     if test_root is None:
+#         return False, {}
+#
+#     exp = Experiment.from_disk(test_root)
+#     if exp.has_prop('tensorboard_args'):
+#         tb = exp.properties.get('tensorboard_args')
+#         metrics = parse_fron_tensorboard(tb['log_dir'])
+#     elif exp.has_prop('logger_args'):
+#         tb = exp.properties.get('logger_args')
+#         metrics = parse_from_log(tb['log_dir'])
+#     else:
+#         fs = [i for i in os.listdir(exp.test_root)]
+#         if len([f for f in fs if f.endswith('.log')]) > 0:
+#             metrics = parse_from_log(os.path.join(exp.test_root, fs[0]))
+#         else:
+#             metrics = {}
+#     return True, metrics
 
 
 def parse_from_log(log) -> Dict[str, List[Step]]:

From e6302268b5b315a69b125510ec7e111d64a8a631 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 14:48:46 +0800
Subject: [PATCH 14/95] Reference update

---
 src/lumo/trainer/callbacks.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lumo/trainer/callbacks.py b/src/lumo/trainer/callbacks.py
index 2f71b22..1018254 100644
--- a/src/lumo/trainer/callbacks.py
+++ b/src/lumo/trainer/callbacks.py
@@ -805,7 +805,7 @@ class SkipWhenParamsEq(TrainCallback, InitialCallback):
     def on_hooked(self, source: Trainer, params: ParamsType):
         super().on_hooked(source, params)
         from dbrecord import PDict
-        from lumo.exp.finder import is_test_root
+        from lumo.exp.watch import is_test_root
         self.fn = source.exp.mk_rpath('contrib', 'params_key.sqlite')
         olds = PDict(self.fn)
 

From c6f5fcefad5b44ef4e17261db7c1eb9d04b5ffc6 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 18:15:27 +0800
Subject: [PATCH 15/95] optional for load DataFrame, lazy load pandas module

---
 src/lumo/exp/watch.py | 15 +++++++++------
 1 file changed, 9 insertions(+), 6 deletions(-)

diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index 06fa476..7ca031b 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -24,7 +24,7 @@
 import re
 from typing import List, Dict, overload
 from pprint import pformat
-import pandas as pd
+
 from dbrecord import PDict
 from datetime import datetime
 from operator import gt, ge, le, lt, eq, ne
@@ -247,7 +247,7 @@ def update(self):
             dic.flush()
         return updates
 
-    def load(self):
+    def load(self, with_pandas=True):
         """
         Loads the experiment information from heartbeat files and the experiment databases.
 
@@ -270,10 +270,13 @@ def load(self):
                 for test in updates[exp_name]:
                     res[test['test_name']] = test
                 dic.flush()
-
-        df = pd.DataFrame(res.values())
-        df = df.sort_values(['exp_name', 'test_name'])
-        return df.reset_index(drop=True)
+        if with_pandas:
+            import pandas as pd
+            df = pd.DataFrame(res.values())
+            df = df.sort_values(['exp_name', 'test_name'])
+            return df.reset_index(drop=True)
+        else:
+            return res
 
     def progress(self, is_alive=True):
         """

From b4d999f73b29c9ddc395e5db758115c9f0c8cff6 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 18:17:00 +0800
Subject: [PATCH 16/95] optional for load DataFrame, lazy load pandas module

---
 src/lumo/exp/watch.py | 15 +++++++++++++--
 1 file changed, 13 insertions(+), 2 deletions(-)

diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index 7ca031b..0d161da 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -251,8 +251,14 @@ def load(self, with_pandas=True):
         """
         Loads the experiment information from heartbeat files and the experiment databases.
 
+        Args:
+            with_pandas (bool, optional): whether to return the experiment information as a pandas DataFrame.
+                Defaults to True.
+
         Returns:
-            A pandas DataFrame containing the experiment information sorted by experiment name and test name.
+            If with_pandas is True, returns a pandas DataFrame containing the experiment information
+            sorted by experiment name and test name. Otherwise, returns a dictionary containing the
+            experiment information.
         """
         res = {}
         updates = self.update()
@@ -271,7 +277,12 @@ def load(self, with_pandas=True):
                     res[test['test_name']] = test
                 dic.flush()
         if with_pandas:
-            import pandas as pd
+            try:
+                import pandas as pd
+            except ImportError as e:
+                print(
+                    'with_padnas=True requires pandas to be installed, use pip install pandas or call `.load(with_padnas=False)`')
+
             df = pd.DataFrame(res.values())
             df = df.sort_values(['exp_name', 'test_name'])
             return df.reset_index(drop=True)

From 1102e8895910204aa329354dbdf0bacf7757f332 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 18:58:32 +0800
Subject: [PATCH 17/95] optional for load DataFrame, lazy load pandas module

---
 src/lumo/exp/watch.py | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index 0d161da..a7f2e82 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -263,6 +263,9 @@ def load(self, with_pandas=True):
         res = {}
         updates = self.update()
 
+        def valid_row(dic):
+            return isinstance(dic, dict) and 'test_name' in dic
+
         for dic_fn in os.listdir(self.db_root):
             if not dic_fn.endswith('sqlite'):
                 continue
@@ -270,12 +273,15 @@ def load(self, with_pandas=True):
             exp_name = os.path.splitext(dic_fn)[0]
 
             for test_name, test_prop in dic.items():
-                res[test_name] = test_prop
+                if valid_row(test_prop):
+                    res[test_name] = test_prop
 
             if exp_name in updates:
                 for test in updates[exp_name]:
-                    res[test['test_name']] = test
+                    if valid_row(test):
+                        res[test['test_name']] = test
                 dic.flush()
+
         if with_pandas:
             try:
                 import pandas as pd

From 512378d0c71b0831debd45fb555e77b11c316401 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 20:05:58 +0800
Subject: [PATCH 18/95] Add scripts for generate shell scripts for multiple
 tests

---
 src/lumo/contrib/scan.py | 72 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 72 insertions(+)
 create mode 100644 src/lumo/contrib/scan.py

diff --git a/src/lumo/contrib/scan.py b/src/lumo/contrib/scan.py
new file mode 100644
index 0000000..b277b0f
--- /dev/null
+++ b/src/lumo/contrib/scan.py
@@ -0,0 +1,72 @@
+"""
+基线对比
+"""
+import time
+from itertools import cycle
+from typing import List
+import torch
+
+from lumo import Params, Logger
+import sys
+
+DATE_FLAG = '2023.03.04'
+
+
+class ScanBaseParams(Params):
+
+    def __init__(self):
+        super().__init__()
+        self.gpus = None
+        self.group_code = None
+        self.interval = 5  # sleep interval between two tests
+
+
+def format_args(**kwargs):
+    return ' '.join([f'--{k}={v}' for k, v in kwargs.items()])
+
+
+def base_main(pm: ScanBaseParams, files: List[str], dics: List[dict]):
+    assert isinstance(pm, ScanBaseParams)
+    log = Logger()
+    log.use_stdout = False
+    log.add_log_dir(f'./log_{pm.group_code}')
+
+    base = ("sleep {sleep} ; " +
+            sys.executable +
+            " {file}.py {kwargs} --device={device}{group} & \n"
+            )
+
+    if not torch.cuda.is_available():
+        gpus = ['cpu']
+    elif pm.gpus is None:
+        gpus = list(range(torch.cuda.device_count()))
+    elif isinstance(pm.gpus, (int, str)):
+        gpus = [torch.device(pm.gpus).index]
+    else:
+        gpus = pm.gpus
+
+    # append None to identity loop end.
+    gpus.append(None)
+    gpus = cycle(gpus)
+    c = 0
+    for i, (file, kwargs) in enumerate(zip(files, dics)):
+        device = next(gpus)
+        if device is None:
+            # wait until all devices are free.
+            c = 0
+            print('wait', flush=True)
+            device = next(gpus)
+
+        if pm.group_code is not None:
+            group = f" --group={pm.group_code} "
+        else:
+            group = ''
+
+        cur = base.format(
+            sleep=c * pm.interval,
+            file=file, kwargs=format_args(**kwargs),
+            device=device, group=group)
+        c += 1
+        log.info(cur.strip())
+        print(cur, flush=True, end='')
+    print('wait', flush=True)

From 4df80806547ed6e4b48b47e4d7b44ad1afd860f9 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 20:07:08 +0800
Subject: [PATCH 19/95] Add scripts for generate shell scripts for multiple
 tests

---
 src/lumo/contrib/scan.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lumo/contrib/scan.py b/src/lumo/contrib/scan.py
index b277b0f..b850109 100644
--- a/src/lumo/contrib/scan.py
+++ b/src/lumo/contrib/scan.py
@@ -17,7 +17,7 @@ class ScanBaseParams(Params):
     def __init__(self):
         super().__init__()
         self.gpus = None
-        self.group_code = None
+        self.group = None
         self.interval = 5  # sleep interval between two tests
 
 

From 5b0a60cc74d05a50e3f9f5e38eb3bca422a44745 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 20:07:34 +0800
Subject: [PATCH 20/95] Add scripts for generate shell scripts for multiple
 tests

---
 src/lumo/contrib/scan.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/src/lumo/contrib/scan.py b/src/lumo/contrib/scan.py
index b850109..247cb65 100644
--- a/src/lumo/contrib/scan.py
+++ b/src/lumo/contrib/scan.py
@@ -29,7 +29,7 @@ def base_main(pm: ScanBaseParams, files: List[str], dics: List[dict]):
     assert isinstance(pm, ScanBaseParams)
     log = Logger()
     log.use_stdout = False
-    log.add_log_dir(f'./log_{pm.group_code}')
+    log.add_log_dir(f'./log_{pm.group}')
 
     base = ("sleep {sleep} ; " +
             sys.executable +
@@ -57,8 +57,8 @@ def base_main(pm: ScanBaseParams, files: List[str], dics: List[dict]):
             print('wait', flush=True)
             device = next(gpus)
 
-        if pm.group_code is not None:
-            group = f" --group={pm.group_code} "
+        if pm.group is not None:
+            group = f" --group={pm.group} "
         else:
             group = ''
 

From 5f529571364d790ca4ea831ddf83285fdc1ffc97 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 20:28:43 +0800
Subject: [PATCH 21/95] Update

---
 src/lumo/exp/experiment.py   |  2 +-
 src/lumo/exp/watch.py        |  7 +++++--
 src/lumo/trainer/trainer.py  |  9 +++++----
 src/lumo/utils/repository.py |  2 +-
 src/lumo/utils/safe_io.py    | 16 ++++++++++++++++
 5 files changed, 28 insertions(+), 8 deletions(-)

diff --git a/src/lumo/exp/experiment.py b/src/lumo/exp/experiment.py
index f2b7999..8ec1646 100644
--- a/src/lumo/exp/experiment.py
+++ b/src/lumo/exp/experiment.py
@@ -449,9 +449,9 @@ def dump_progress(self, ratio: float, update_from=None):
             update_from: The process from which the progress update came from.
         """
         res = {'ratio': max(min(ratio, 1), 0)}
+        res['last_edit_time'] = strftime()
         if update_from is None:
             res['update_from'] = update_from
-            res['last_edit_time'] = strftime()
         self.dump_info('progress', res, append=True)
 
     def dump_info(self, key: str, info: Any, append=False):
diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index a7f2e82..44a4dc3 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -295,7 +295,7 @@ def valid_row(dic):
         else:
             return res
 
-    def progress(self, is_alive=True):
+    def progress(self, is_alive=True, with_pandas=True):
         """
         Returns a DataFrame of alive experiments.
 
@@ -323,7 +323,10 @@ def progress(self, is_alive=True):
                                       )
                 except:
                     continue
-        return pd.DataFrame(res)
+        if with_pandas:
+            return pd.DataFrame(res)
+        else:
+            return res
 
     def interactive(self):
         """interactive, mark, label, note in ipython environment."""
diff --git a/src/lumo/trainer/trainer.py b/src/lumo/trainer/trainer.py
index 93b700d..1024a04 100644
--- a/src/lumo/trainer/trainer.py
+++ b/src/lumo/trainer/trainer.py
@@ -22,6 +22,7 @@
 from lumo.data.loader import DataLoaderType, DataLoaderSide
 from lumo.proc import dist
 from lumo.proc import glob
+from lumo.utils import safe_io as IO
 from lumo.trainer.rnd import RndManager
 from lumo.utils.logger import Logger
 from .base import _BaseTrainer
@@ -1036,8 +1037,8 @@ def save_best_model(self):
 
         torch.save(self.state_dict(), file)
 
-        with open(file_info, 'w') as w:
-            w.write(json.dumps({'global_steps': self.global_steps, 'metric': self.exp.metric.value}))
+        res = {'global_steps': self.global_steps, 'metric': self.exp.metric.value}
+        IO.dump_json(IO.filter_unserializable_values(res), file_info)
 
         self.logger.info(f'saved best model at {file}')
         self.wait_for_everyone()
@@ -1067,8 +1068,8 @@ def save_last_model(self):
 
         torch.save(self.state_dict(), file)
 
-        with open(file_info, 'w') as w:
-            w.write(json.dumps({'global_steps': self.global_steps, 'metric': self.exp.metric.value}))
+        res = {'global_steps': self.global_steps, 'metric': self.exp.metric.value}
+        IO.dump_json(IO.filter_unserializable_values(res), file_info)
 
         self.logger.info(f'saved last model at {file}')
         self.wait_for_everyone()
diff --git a/src/lumo/utils/repository.py b/src/lumo/utils/repository.py
index 6466ab7..fce12f8 100644
--- a/src/lumo/utils/repository.py
+++ b/src/lumo/utils/repository.py
@@ -55,7 +55,7 @@ class branch:
 
     def __init__(self, repo: Repo, branch: str):
         self.repo = repo
-        self.lock = Lock(f'{hash(repo.git_dir)}_{branch}')
+        self.lock = Lock(f'{hash(repo.git_dir)}_lumo_auto_commit')
         self.lock.abtain()
         self.old_branch = self.repo.head.reference
         self.branch = branch
diff --git a/src/lumo/utils/safe_io.py b/src/lumo/utils/safe_io.py
index b87d588..2fbaf69 100644
--- a/src/lumo/utils/safe_io.py
+++ b/src/lumo/utils/safe_io.py
@@ -16,6 +16,22 @@
 load_nd = load_nd
 
 
+def filter_unserializable_values(self, d):
+    for key, value in list(d.items()):
+        if isinstance(value, dict):
+            filter_unserializable_values(value)
+        elif isinstance(value, list):
+            for i in range(len(value)):
+                if isinstance(value[i], dict):
+                    filter_unserializable_values(value[i])
+                elif not json.dumps(value[i], default=lambda x: None):
+                    value[i] = None
+        elif not json.dumps(value, default=lambda x: None):
+            d[key] = None
+    d = {key: value for key, value in d.items() if value is not None}
+    return d
+
+
 def dump_json(obj, fn):
     """
     Dumps the given object to a JSON file at the given file path.

From ce772dba0673ae6e87d89cc0abe76957b9a539a8 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 20:31:32 +0800
Subject: [PATCH 22/95] Update

---
 src/lumo/utils/safe_io.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/src/lumo/utils/safe_io.py b/src/lumo/utils/safe_io.py
index 2fbaf69..51306d2 100644
--- a/src/lumo/utils/safe_io.py
+++ b/src/lumo/utils/safe_io.py
@@ -16,8 +16,8 @@
 load_nd = load_nd
 
 
-def filter_unserializable_values(self, d):
-    for key, value in list(d.items()):
+def filter_unserializable_values(dic):
+    for key, value in list(dic.items()):
         if isinstance(value, dict):
             filter_unserializable_values(value)
         elif isinstance(value, list):
@@ -27,9 +27,9 @@ def filter_unserializable_values(self, d):
                 elif not json.dumps(value[i], default=lambda x: None):
                     value[i] = None
         elif not json.dumps(value, default=lambda x: None):
-            d[key] = None
-    d = {key: value for key, value in d.items() if value is not None}
-    return d
+            dic[key] = None
+    dic = {key: value for key, value in dic.items() if value is not None}
+    return dic
 
 
 def dump_json(obj, fn):

From 40c735c8b51052a9b531137404e1e5aeee5e6b3c Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 20:38:17 +0800
Subject: [PATCH 23/95] Update

---
 src/lumo/exp/metric.py      | 12 +++++++++++-
 src/lumo/trainer/trainer.py |  2 +-
 src/lumo/utils/safe_io.py   |  2 +-
 3 files changed, 13 insertions(+), 3 deletions(-)

diff --git a/src/lumo/exp/metric.py b/src/lumo/exp/metric.py
index e7e9fdd..56cc574 100644
--- a/src/lumo/exp/metric.py
+++ b/src/lumo/exp/metric.py
@@ -27,10 +27,16 @@ def __init__(self, metric_fn, persistent=True):
         os.makedirs(os.path.dirname(os.path.abspath(metric_fn)), exist_ok=True)
         self.fn = metric_fn
         self._metric = {}
+        self._last = {}
         if os.path.exists(metric_fn):
             self._metric = IO.load_pkl(metric_fn)
+
         self.persistent = persistent
 
+    @property
+    def current(self):
+        return self._last
+
     @property
     def value(self):
         """
@@ -63,7 +69,7 @@ def dump_metric(self, key, value, cmp: str, flush=True, **kwargs):
         Raises:
             NotImplementedError: If cmp is not 'max' or 'min'.
         """
-        dic = self.value
+        dic = self._metric
         older = dic.setdefault(key, None)
 
         update = False
@@ -86,6 +92,10 @@ def dump_metric(self, key, value, cmp: str, flush=True, **kwargs):
         else:
             value = older
 
+        self._last[key] = value
+        for kk, vv in kwargs.items():
+            self._last[kk] = vv
+
         if flush:
             self.flush()
         return value
diff --git a/src/lumo/trainer/trainer.py b/src/lumo/trainer/trainer.py
index 1024a04..98ee368 100644
--- a/src/lumo/trainer/trainer.py
+++ b/src/lumo/trainer/trainer.py
@@ -1068,7 +1068,7 @@ def save_last_model(self):
 
         torch.save(self.state_dict(), file)
 
-        res = {'global_steps': self.global_steps, 'metric': self.exp.metric.value}
+        res = {'global_steps': self.global_steps, 'metric': self.exp.metric.current}
         IO.dump_json(IO.filter_unserializable_values(res), file_info)
 
         self.logger.info(f'saved last model at {file}')
diff --git a/src/lumo/utils/safe_io.py b/src/lumo/utils/safe_io.py
index 51306d2..434f189 100644
--- a/src/lumo/utils/safe_io.py
+++ b/src/lumo/utils/safe_io.py
@@ -26,7 +26,7 @@ def filter_unserializable_values(dic):
                     filter_unserializable_values(value[i])
                 elif not json.dumps(value[i], default=lambda x: None):
                     value[i] = None
-        elif not json.dumps(value, default=lambda x: None):
+        elif json.dumps(value, default=lambda x: None) == 'null':
             dic[key] = None
     dic = {key: value for key, value in dic.items() if value is not None}
     return dic

From 58834764abb9ede4c93f18d8abe0bb1893330167 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 20:47:19 +0800
Subject: [PATCH 24/95] Add timezone

---
 src/lumo/exp/watch.py         | 3 ++-
 src/lumo/proc/tz.py           | 6 ++++++
 src/lumo/trainer/callbacks.py | 4 ++--
 src/lumo/utils/fmt.py         | 3 ++-
 src/lumo/utils/logger.py      | 2 +-
 5 files changed, 13 insertions(+), 5 deletions(-)
 create mode 100644 src/lumo/proc/tz.py

diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index 44a4dc3..f13dc2e 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -33,6 +33,7 @@
 from .experiment import Experiment
 from lumo.utils import safe_io as IO
 from lumo.utils.fmt import format_timedelta, strptime, strftime
+from lumo.proc.tz import timezone
 
 PID_ROOT = os.path.join(progressroot(), 'pid')
 HB_ROOT = os.path.join(progressroot(), 'hb')
@@ -394,7 +395,7 @@ def on_tag_update(sender):
             tag_ui = widgets.TagsInput(value=tags)
             tag_ui.observe(on_tag_update, names='value', type='change')
 
-            now = datetime.now()
+            now = datetime.now(timezone())
             start = strptime(datestr=dic['progress']['start'])
             end = strptime(datestr=dic['progress']['last_edit_time'])
 
diff --git a/src/lumo/proc/tz.py b/src/lumo/proc/tz.py
new file mode 100644
index 0000000..9af8dac
--- /dev/null
+++ b/src/lumo/proc/tz.py
@@ -0,0 +1,6 @@
+from .config import glob
+import pytz
+
+
+def timezone():
+    return pytz.timezone(glob.get('timezone'), 'Asia/Shanghai')
diff --git a/src/lumo/trainer/callbacks.py b/src/lumo/trainer/callbacks.py
index 1018254..5889016 100644
--- a/src/lumo/trainer/callbacks.py
+++ b/src/lumo/trainer/callbacks.py
@@ -9,7 +9,7 @@
 from datetime import datetime
 from functools import wraps
 from typing import NewType, Any, Optional, Dict, Union
-
+from lumo.proc.tz import timezone
 import psutil
 from torch.utils.data import DataLoader
 
@@ -707,7 +707,7 @@ def request(self, data: dict):
         task = self.executor.submit(self.req.post, self.url, json={'data': data,
                                                                    'type': 'timeevent',
                                                                    'from': 'lumo.RemoteCallback',
-                                                                   'datetime': datetime.now().isoformat()})
+                                                                   'datetime': datetime.now(timezone()).isoformat()})
         self.submits.append(task)
 
     def on_hooked(self, source: Trainer, params: ParamsType):
diff --git a/src/lumo/utils/fmt.py b/src/lumo/utils/fmt.py
index ef6c537..8a52711 100644
--- a/src/lumo/utils/fmt.py
+++ b/src/lumo/utils/fmt.py
@@ -6,6 +6,7 @@
 
 import numpy as np
 import torch
+from lumo.proc.tz import timezone
 
 from . import re
 
@@ -42,7 +43,7 @@ def strftime(fmt='%y-%m-%d-%H%M%S', dateobj: datetime = None):
     """get current date with formatted"""
     if dateobj is not None:
         return dateobj.strftime(fmt)
-    return datetime.now().strftime(fmt)
+    return datetime.now(timezone()).strftime(fmt)
 
 
 def strptime(datestr: str = None, fmt='%y-%m-%d-%H%M%S', ):
diff --git a/src/lumo/utils/logger.py b/src/lumo/utils/logger.py
index 04c3e4f..893db2e 100644
--- a/src/lumo/utils/logger.py
+++ b/src/lumo/utils/logger.py
@@ -128,7 +128,7 @@ def _format(self, *values, inline=False, fix=0, raw=False, append=False, level=V
             return None, None
 
         if self.adddate and not raw:
-            cur_date = datetime.now().strftime(self.datefmt)
+            cur_date = strftime(self.datefmt)
         else:
             cur_date = ""
 

From 8cdcc72aa1c7443490ff0479e6e3529f27eab0cc Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 20:52:13 +0800
Subject: [PATCH 25/95] Add timezone

---
 src/lumo/proc/tz.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lumo/proc/tz.py b/src/lumo/proc/tz.py
index 9af8dac..fb89bec 100644
--- a/src/lumo/proc/tz.py
+++ b/src/lumo/proc/tz.py
@@ -3,4 +3,4 @@
 
 
 def timezone():
-    return pytz.timezone(glob.get('timezone'), 'Asia/Shanghai')
+    return pytz.timezone(glob.get('timezone', 'Asia/Shanghai'))

From 7ec89348cde5cdfd589659de6d0a113b92eef10a Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 20:57:39 +0800
Subject: [PATCH 26/95] Add timezone

---
 src/lumo/contrib/scan.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lumo/contrib/scan.py b/src/lumo/contrib/scan.py
index 247cb65..2155572 100644
--- a/src/lumo/contrib/scan.py
+++ b/src/lumo/contrib/scan.py
@@ -33,7 +33,7 @@ def base_main(pm: ScanBaseParams, files: List[str], dics: List[dict]):
 
     base = ("sleep {sleep} ; " +
             sys.executable +
-            " {file}.py {kwargs} --device={device}{group} & \n"
+            " {file} {kwargs} --device={device}{group} & \n"
             )
 
     if not torch.cuda.is_available():

From 56ff87d9cb0c04815e3dacbb0fad74d001708430 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Mon, 13 Mar 2023 23:09:35 +0800
Subject: [PATCH 27/95] Flake8 error fixed

---
 src/lumo/exp/watch.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index f13dc2e..e6ffa0c 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -172,6 +172,7 @@ def mask(self, df):
         Returns:
             A boolean mask of the given DataFrame based on the condition.
         """
+        import pandas as pd
         names = self.name.split('.')
         value = df
         for i in names:
@@ -224,7 +225,7 @@ def update(self):
         """Diff & Update"""
         updates = {}
         if not os.path.exists(self.hb_root):
-            return pd.DataFrame()
+            return {}
         for root, dirs, fs in os.walk(self.hb_root):
             if root == self.hb_root:
                 continue
@@ -325,6 +326,7 @@ def progress(self, is_alive=True, with_pandas=True):
                 except:
                     continue
         if with_pandas:
+            import pandas as pd
             return pd.DataFrame(res)
         else:
             return res
@@ -359,7 +361,7 @@ def widget(self,
         assert params_filter is None or isinstance(params_filter, list)
         assert metric_filter is None or isinstance(metric_filter, list)
 
-        from ipywidgets import widgets, interact, Label
+        from ipywidgets import widgets, interact
         from IPython.display import display
 
         def make_row(dic: dict):

From 03ea68a0f05ef4f142698d90918e6d1cb07c57ae Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Tue, 14 Mar 2023 10:45:23 +0800
Subject: [PATCH 28/95] rerun cli find test by watcher

---
 src/lumo/cli/__init__.py | 15 ++++++++++-----
 1 file changed, 10 insertions(+), 5 deletions(-)

diff --git a/src/lumo/cli/__init__.py b/src/lumo/cli/__init__.py
index 714545e..d48da03 100644
--- a/src/lumo/cli/__init__.py
+++ b/src/lumo/cli/__init__.py
@@ -13,12 +13,17 @@ def rerun(test_name, **kwarg):
     Returns:
 
     """
-    from lumo.exp.finder import retrieval_experiment
-    exp = retrieval_experiment(test_name)
-    if exp is not None:
-        exp.rerun([f'--{k}={v}' for k, v in kwarg.items()])
-    else:
+    from lumo.exp.watch import Watcher
+    from lumo import Experiment
+    w = Watcher()
+    df = w.load()
+    df = df[df['test_name'] == test_name]
+    if len(df) == 0:
+        print(f'{test_name} not found')
         exit(1)
+    else:
+        exp = Experiment.from_cache(df.iloc[0].to_dict())
+        exp.rerun([f'--{k}={v}' for k, v in kwarg.items()])
 
 
 def note(test_name, description):

From cc983380c444b25f69b8da0c2c43f303c71af367 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Tue, 14 Mar 2023 11:02:35 +0800
Subject: [PATCH 29/95] rerun cli find test by watcher

---
 src/lumo/exp/experiment.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/src/lumo/exp/experiment.py b/src/lumo/exp/experiment.py
index 8ec1646..e949811 100644
--- a/src/lumo/exp/experiment.py
+++ b/src/lumo/exp/experiment.py
@@ -697,10 +697,10 @@ def rerun(self, arg_list: List[str]):
         new_test_name = self._create_test_name(self.exp_dir)
         new_exp = Experiment(self.exp_name, test_name=new_test_name)
         self.dump_info('deprecated', {'rerun_at': {new_exp.test_name: True}}, append=True)
-        old_rerun_info = self.properties.get('rerun', None)
+        old_rerun_info = self.properties.get('rerun', {})
         count = 1
-        if old_rerun_info is not None:
-            count += old_rerun_info['count']
+        if isinstance(old_rerun_info, dict):
+            count += old_rerun_info.get('repeat', 0)
         new_exp.dump_info('rerun', {'from': self.test_name, 'repeat': count})
         from lumo.utils.subprocess import run_command
         old_exec = self.properties['execute']

From fa0ac339257c71b3f1841f523d4d201ff948470c Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 10:19:41 +0800
Subject: [PATCH 30/95] Add panel for Experiment

---
 src/lumo/exp/experiment.py    |  13 ++-
 src/lumo/exp/exphook.py       |  10 +-
 src/lumo/exp/lazy_panel.py    | 169 ++++++++++++++++++++++++++++++++++
 src/lumo/exp/watch.py         |  31 +++----
 src/lumo/trainer/callbacks.py |   1 +
 src/lumo/utils/subprocess.py  |  14 ++-
 6 files changed, 213 insertions(+), 25 deletions(-)
 create mode 100644 src/lumo/exp/lazy_panel.py

diff --git a/src/lumo/exp/experiment.py b/src/lumo/exp/experiment.py
index e949811..b941a69 100644
--- a/src/lumo/exp/experiment.py
+++ b/src/lumo/exp/experiment.py
@@ -122,6 +122,7 @@ def __init__(self, exp_name: str, test_name=None, paths=None):
         self.dump_string = self._trigger_change(self.dump_string)
         self.dump_note = self._trigger_change(self.dump_note)
         self.dump_info = self._trigger_change(self.dump_info)
+        self.trigger = self._trigger_change(self.trigger)
 
         self.logger = Logger()
 
@@ -365,6 +366,9 @@ def exec_argv(self):
         except:
             return []
 
+    def trigger(self):
+        pass
+
     def _trigger_change(self, func):
         """
         Decorator function that updates the heartbeat file before executing the decorated function.
@@ -384,6 +388,7 @@ def inner(*args, **kwargs):
             """wrap function"""
             fn = self.heartbeat_fn
             io.dump_text(self.info_dir, fn)
+            io.dump_text(self.info_dir, self.pid_fn)
             return func(*args, **kwargs)
 
         return inner
@@ -731,11 +736,13 @@ def initial(self):
             'obj': runtime_pid_obj(),
         })
 
+        self.dump_tags([])
+
         # register start
         self.dump_info('progress', {'start': strftime(), 'finished': False}, append=True)
         self.dump_progress(0)
         # register progress
-        io.dump_text(self.info_dir, self.pid_fn)
+
         self.add_exit_hook(self.end)
 
     @call_on_main_process_wrap
@@ -746,7 +753,6 @@ def start(self):
         if self.properties.get('progress', None) is not None:
             return
         self.initial()
-        self.set_prop('start', True)
         for hook in self._hooks.values():  # type: BaseExpHook
             hook.on_start(self)
         return self
@@ -761,14 +767,11 @@ def end(self, end_code=0, *args, **extra):
             *args: Additional arguments to pass to the end hooks.
             **extra: Additional keyword arguments to pass to the end hooks.
         """
-        if not self.is_alive:
-            return
         if not self.properties.get('progress', None) is None:
             return
         if self.properties['progress'].get('end', False):
             return
 
-        self.set_prop('end', True)
         if end_code == 0:
             self.dump_progress(1)
 
diff --git a/src/lumo/exp/exphook.py b/src/lumo/exp/exphook.py
index 68500fb..2184b3e 100644
--- a/src/lumo/exp/exphook.py
+++ b/src/lumo/exp/exphook.py
@@ -89,10 +89,14 @@ def exc_end(self, exc_type, exc_val, exc_tb):
         import traceback
         res = traceback.format_exception(exc_type, exc_val, exc_tb)
         res = [i for i in res if 'in _newfunc' not in i]
-        self.exp.dump_string('exception', "".join(res))
+
+        self.exp.dump_info('exception', {
+            'exception_type': traceback.format_exception_only(exc_type, exc_val)[-1].strip(),
+            'exception_content': "".join(res)
+        })
+
         self.exp.end(
-            end_code=1,
-            exc_type=traceback.format_exception_only(exc_type, exc_val)[-1].strip()
+            end_code=1
         )
 
 
diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
new file mode 100644
index 0000000..819978e
--- /dev/null
+++ b/src/lumo/exp/lazy_panel.py
@@ -0,0 +1,169 @@
+try:
+    import panel as pn
+except ImportError as e:
+    raise ImportError('') from e
+from typing import Any
+
+from bokeh.core.property.primitive import String
+from bokeh.plotting import figure
+import pandas as pd
+from panel.models.tabulator import TableEditEvent
+
+from lumo.exp.watch import Watcher
+import datetime as dt
+import numpy as np
+from bokeh.models.widgets.tables import HTMLTemplateFormatter, NumberFormatter, TextEditor, StringEditor
+from lumo import Experiment
+
+css = '''
+.tabulator-tableholder {
+ height: fit-content !important;
+}
+
+.tabulator-row .tabulator-cell {
+  overflow: visible !important;
+  vertical-align: top;
+  min-height: 20px;
+}
+.bk {
+
+}
+.tabulator .tabulator-col-resize-handle {
+ height: fit-content !important;
+
+}
+
+.tabulator-cell .tabulator-editable {
+ width: fit-content !important;
+ 
+}
+
+'''
+
+pn.extension('tabulator', raw_css=[css], css_files=[pn.io.resources.CSS_URLS['font-awesome']])
+
+
+def DictFormatter(column_name):
+    base_template = """
+    <details style="overflow: visible;">
+        <summary>{column_name}</summary>
+        <% _.each(value, function(vv, key) { %>
+            <li><b><%= key %>:</b> <%= vv %></li>
+        <% }); %>
+    </details>"""
+    return HTMLTemplateFormatter(template=base_template.replace('{column_name}', column_name))
+
+
+class ExceptionFormatter:
+    base_template = """
+<details style="overflow: visible;">
+    <summary> 
+        <%= value['exception_type'] %> 
+    </summary>
+    <p style='display: inherit;white-space: break-spaces;word-wrap: normal;word-break: break-all;'> 
+        <%= value['exception_content'] %> 
+    </p>
+</details>"""
+
+
+long_text = HTMLTemplateFormatter(template=
+                                  """
+                     <details
+                        style = "overflow: visible;" >
+                     <summary > < % value['exception_type'] % > < / summary >
+                     < p
+                     style = 'display: inherit;white-space: break-spaces;word-wrap: normal;word-break: break-all;' >
+                     < %-  exception_content % >
+                     < / p >
+                     < / details >
+                     """)
+
+tabulator_formatters = {
+    'metrics': DictFormatter(column_name='metrics'),
+    'progress': DictFormatter(column_name='progress'),
+    'params': DictFormatter(column_name='params'),
+    'exception': HTMLTemplateFormatter(template=ExceptionFormatter.base_template),
+}
+
+tabulator_editors = {
+    'exp_name': None,
+    'test_name': None,
+    'params': None,
+    'metrics': None,
+    'progress': None,
+    'exception': None,
+    'str': {'type': 'list', 'valuesLookup': True},
+    # 'note': TextEditor(),
+    # 'tags': StringEditor(),
+}
+
+
+def make_experiment_tabular(df: pd.DataFrame, reload_fn):
+    """
+    {'start': '23-03-14-224651',
+     'finished': False,
+     'ratio': 0,
+     'last_edit_time': '23-03-14-224651',
+     'update_from': None}
+
+    Args:
+        df:
+        reload_fn:
+
+    Returns:
+
+    """
+    # process exception
+    if 'exception' not in df.columns:
+        df['exception'] = {}
+    else:
+        df['exception'].fillna({})
+
+    # process progress
+    ratio = df['progress'].apply(lambda x: x.get('ratio', 0))
+    end_code = df['progress'].apply(lambda x: x.get('end_code', None))
+
+    # ratio = 1
+    # ratio < 1, no-end-code ->
+
+    df = df[[
+        'exp_name', 'test_name',
+        'progress',
+        'exception',
+        'params', 'metrics',
+        'note', 'tags',
+    ]]
+
+    def on_cell_change(e: TableEditEvent):
+        nonlocal df
+        if e.column == 'note':
+            Experiment.from_cache(df.iloc[e.row].to_dict()).dump_note(e.value)
+        else:
+            tags = [i.strip() for i in e.value.split(',')]
+            Experiment.from_cache(df.iloc[e.row].to_dict()).dump_tags(tags)
+
+        df = reload_fn()
+
+    df_widget = pn.widgets.Tabulator(
+        df,
+        groupby=['exp_name'],
+        hidden_columns=['git', 'paths', 'pinfo',
+                        'execute', 'lock', 'params.yaml',
+                        'params_hash', 'table_row', 'hooks', 'logger_args',
+                        'metric_board'],
+        pagination='local',
+        formatters=tabulator_formatters,
+        editors=tabulator_editors,
+        selection=[],
+        show_index=False,
+        configuration={
+            'clipboard': True,
+            # 'rowHeight': 100,
+            # 'columnDefaults': {
+            #     'headerSort': False,
+            #     },
+        }
+    )
+
+    df_widget.on_edit(on_cell_change)
+    return df_widget
diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index e6ffa0c..fe88874 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -34,6 +34,7 @@
 from lumo.utils import safe_io as IO
 from lumo.utils.fmt import format_timedelta, strptime, strftime
 from lumo.proc.tz import timezone
+from lumo.proc import glob
 
 PID_ROOT = os.path.join(progressroot(), 'pid')
 HB_ROOT = os.path.join(progressroot(), 'hb')
@@ -240,6 +241,8 @@ def update(self):
                         raise e
                     except:
                         continue
+                    finally:
+                        os.remove(hb_file)
 
         for exp_name, tests in updates.items():
             dic = PDict(os.path.join(self.db_root, f'{exp_name}.sqlite'))
@@ -297,7 +300,7 @@ def valid_row(dic):
         else:
             return res
 
-    def progress(self, is_alive=True, with_pandas=True):
+    def progress(self, with_pandas=True):
         """
         Returns a DataFrame of alive experiments.
 
@@ -313,16 +316,23 @@ def progress(self, is_alive=True, with_pandas=True):
                 if not f.endswith('.pid'):
                     continue
                 try:
-                    test_root = IO.load_text(os.path.join(root, f))
+                    pid_f = os.path.join(root, f)
+                    test_root = IO.load_text(pid_f)
                     exp = Experiment.from_disk(test_root)
-                    if exp.is_alive == is_alive:
+
+                    if exp.is_alive:
                         res.append(exp.dict())
-                    if not exp.is_alive and exp.properties['progress'].get('finished', None) is None:
+                    elif exp.properties['progress'].get('finished', None) is None:
+                        if (datetime.timestamp(datetime.now()) - os.stat(pid_f).st_mtime) < glob.get(
+                                'ALIVE_SECONDS', 1800):
+                            res.append(exp.dict())
+                    else:
                         exp.dump_info('progress',
                                       {
-                                          'end': strftime(), 'finished': True, 'end_code': -1,
+                                          'end': strftime(), 'finished': True, 'end_code': -10,
                                           'msg': 'ended by watcher'}
                                       )
+                        os.remove(pid_f)
                 except:
                     continue
         if with_pandas:
@@ -339,17 +349,6 @@ def server(self):
         """simple server which make you note your experiments"""
         pass
 
-    def list_all(self, exp_root=None, limit=100) -> Dict[str, List[Experiment]]:
-        """
-        Returns a dictionary of all experiments under exp_root directory.
-
-        Args:
-            exp_root: The root directory to search for experiments. Default is None, which uses the default experiment root directory.
-
-        Returns:
-            A dictionary of all experiments, where the keys are the names of the experiments and the values are lists of corresponding Experiment objects.
-        """
-
     def widget(self,
                is_finished: bool = None,
                is_alive: bool = None,
diff --git a/src/lumo/trainer/callbacks.py b/src/lumo/trainer/callbacks.py
index 5889016..b842d40 100644
--- a/src/lumo/trainer/callbacks.py
+++ b/src/lumo/trainer/callbacks.py
@@ -404,6 +404,7 @@ def update(self, trainer: Trainer):
                 TrainStage.train in self.stage and ((trainer.idx + 1) == self.stage[TrainStage.train])):
             trainer.logger.inline(self.cur_tqdm.full_str())
             trainer.logger.newline()
+            trainer.exp.trigger()
 
     def flush(self, trainer: Trainer):
         """Flush"""
diff --git a/src/lumo/utils/subprocess.py b/src/lumo/utils/subprocess.py
index f1e073d..c610905 100644
--- a/src/lumo/utils/subprocess.py
+++ b/src/lumo/utils/subprocess.py
@@ -4,7 +4,16 @@
 import signal
 
 
-def run_command(command, cwd=None, env=None):
+def consume(p: subprocess.Popen):
+    for stream in [p.stdout, p.stderr]:
+        while True:
+            line = stream.readline().decode('utf-8')
+            if not line:
+                break
+            print(line, end='')
+
+
+def run_command(command, cwd=None, env=None, non_block=False):
     """
     Executes a command in the shell and captures its standard output and standard error.
 
@@ -20,6 +29,9 @@ def run_command(command, cwd=None, env=None):
                             cwd=cwd,
                             env=env,
                             shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+    if non_block:
+        return proc
+
     try:
         while proc.poll() is None:
             # Wait for output from the process

From 10ca8e577490fc015b552b552ba0c1512819a2ea Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 14:59:24 +0800
Subject: [PATCH 31/95] Give full string for better debug experience

---
 src/lumo/utils/safe_io.py | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/src/lumo/utils/safe_io.py b/src/lumo/utils/safe_io.py
index 434f189..0daffc7 100644
--- a/src/lumo/utils/safe_io.py
+++ b/src/lumo/utils/safe_io.py
@@ -43,8 +43,11 @@ def dump_json(obj, fn):
     Notes:
         The JSON data will be written with an indentation of 2 spaces.
     """
-    with open(fn, 'w', encoding='utf-8') as w:
-        json.dump(obj, w, indent=2)
+    try:
+        with open(fn, 'w', encoding='utf-8') as w:
+            json.dump(obj, w, indent=2)
+    except TypeError as e:
+        raise TypeError(str(obj)) from e
 
 
 def dump_yaml(obj, fn):

From f1a81219f95d4dc01ba945d62d9697582fbd949e Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 14:59:34 +0800
Subject: [PATCH 32/95] Panel for experiment

---
 src/lumo/exp/agent.py      |  34 +++++++
 src/lumo/exp/base.py       |   2 +-
 src/lumo/exp/experiment.py |  65 +++++++------
 src/lumo/exp/exphook.py    |   6 +-
 src/lumo/exp/lazy_panel.py |  58 ++++++++----
 src/lumo/exp/watch.py      | 187 ++-----------------------------------
 6 files changed, 125 insertions(+), 227 deletions(-)
 create mode 100644 src/lumo/exp/agent.py

diff --git a/src/lumo/exp/agent.py b/src/lumo/exp/agent.py
new file mode 100644
index 0000000..2ccf33f
--- /dev/null
+++ b/src/lumo/exp/agent.py
@@ -0,0 +1,34 @@
+"""
+heartbeat mechanism
+"""
+import time
+
+import psutil
+from joblib import hash
+
+from lumo.core import BaseParams
+from lumo.utils import safe_io as IO
+from lumo.utils.fmt import strftime
+from lumo.exp import Experiment
+
+
+def wait_pid_stop(info_dir=None):
+    params = BaseParams()
+    params.info_dir = info_dir
+    params.from_args()
+
+    exp = Experiment.from_disk(params.info_dir)
+    pid = exp.properties['pinfo'].get('pid')
+    info_dir = exp.info_dir
+    try:
+        while pid is not None and psutil.pid_exists(pid):
+            exp.trigger()
+            exp.dump_info('agent', {'last_edit_time': strftime()})
+
+            time.sleep(10)
+    except:
+        pass
+
+
+if __name__ == '__main__':
+    wait_pid_stop()
diff --git a/src/lumo/exp/base.py b/src/lumo/exp/base.py
index fbfb056..4fd231a 100644
--- a/src/lumo/exp/base.py
+++ b/src/lumo/exp/base.py
@@ -88,7 +88,7 @@ def on_newpath(self, exp, *args, **kwargs):
 
         """
 
-    def __repr__(self):
+    def __str__(self):
         """Return a string representation of the hook.
 
         Returns:
diff --git a/src/lumo/exp/experiment.py b/src/lumo/exp/experiment.py
index b941a69..203e08b 100644
--- a/src/lumo/exp/experiment.py
+++ b/src/lumo/exp/experiment.py
@@ -19,6 +19,7 @@
 from lumo.utils import safe_io as io
 from lumo.utils.fmt import can_be_filename, strftime
 from lumo.utils.logger import Logger
+from lumo.utils.subprocess import run_command
 from .base import BaseExpHook
 from ..proc.pid import pid_hash, runtime_pid_obj
 from .metric import Metric
@@ -91,7 +92,7 @@ class Experiment:
 
     ENV_TEST_NAME_KEY = 'LUMO_EXP_TEST_NAME'
 
-    def __init__(self, exp_name: str, test_name=None, paths=None):
+    def __init__(self, exp_name: str = None, test_name=None, paths=None, info_dir=None):
         """
         Initializes a new instance of the Experiment class.
 
@@ -106,17 +107,24 @@ def __init__(self, exp_name: str, test_name=None, paths=None):
             raise ValueError(f'Experiment name should be a ligal filename(bettor only contain letter or underline),'
                              f'but got {exp_name}.')
 
-        self._prop = {}
-        self._prop['exp_name'] = exp_name
-        if test_name is None:
-            test_name = os.environ.get(Experiment.ENV_TEST_NAME_KEY, None)
-        self._prop['test_name'] = test_name
-        if paths is None:
-            paths = {}
-        self._prop['paths'] = paths
+        if info_dir is not None:
+            exp = self.__class__.from_disk(info_dir=info_dir)
+            self._prop = exp._prop
+            self._hooks = exp._hooks
+            self._metric = exp._metric
+        else:
+            assert exp_name is not None
+            self._prop = {'exp_name': exp_name}
+            if test_name is None:
+                test_name = os.environ.get(Experiment.ENV_TEST_NAME_KEY, None)
+            self._prop['test_name'] = test_name
+            if paths is None:
+                paths = {}
+            self._prop['paths'] = paths
+            self._prop['note'] = ''
 
-        self._hooks = {}
-        self._metric = None
+            self._hooks = {}
+            self._metric = None
 
         # wrap
         self.dump_string = self._trigger_change(self.dump_string)
@@ -183,7 +191,7 @@ def __repr__(self):
         Returns:
             str: A string representation of the Experiment object.
         """
-        return f'{self.exp_name}->({self.test_name})'
+        return f'{self.__class__.__name__}(info_dir={self.info_dir})'
 
     def __str__(self):
         """
@@ -192,7 +200,7 @@ def __str__(self):
         Returns:
             str: A string representation of the Experiment object.
         """
-        return self.__repr__()
+        return f'{self.__class__.__name__}(info_dir={self.info_dir})'
 
     def _repr_html_(self):
         """Return a html representation for a particular DataFrame."""
@@ -739,9 +747,10 @@ def initial(self):
         self.dump_tags([])
 
         # register start
-        self.dump_info('progress', {'start': strftime(), 'finished': False}, append=True)
+        self.dump_info('progress', {'start': strftime()}, append=True)
         self.dump_progress(0)
         # register progress
+        self.proc = run_command(f'python3 -m lumo.exp.agent --info_dir={self.info_dir}', non_block=True)
 
         self.add_exit_hook(self.end)
 
@@ -767,7 +776,7 @@ def end(self, end_code=0, *args, **extra):
             *args: Additional arguments to pass to the end hooks.
             **extra: Additional keyword arguments to pass to the end hooks.
         """
-        if not self.properties.get('progress', None) is None:
+        if self.properties.get('progress', None) is None:
             return
         if self.properties['progress'].get('end', False):
             return
@@ -775,9 +784,11 @@ def end(self, end_code=0, *args, **extra):
         if end_code == 0:
             self.dump_progress(1)
 
-        self.dump_info('progress', {'end': strftime(), 'finished': True, 'end_code': end_code}, append=True)
+        self.dump_info('progress', {'end': strftime(), 'end_code': end_code}, append=True)
         for hook in self._hooks.values():  # type: BaseExpHook
             hook.on_end(self, end_code=end_code, *args, **extra)
+
+        self.proc.terminate()
         return self
 
     @call_on_main_process_wrap
@@ -813,7 +824,7 @@ def add_exit_hook(self, func):
         import atexit
         def exp_func():
             """Function executed before process exit."""
-            func(self)
+            func()
 
         atexit.register(exp_func)
 
@@ -838,12 +849,12 @@ def from_cache(cls, dic: dict):
         return self
 
     @classmethod
-    def from_disk(cls, path):
+    def from_disk(cls, info_dir):
         """
         Creates an Experiment object from a test root directory on disk.
 
         Args:
-            path (str): The path to the test root directory.
+            info_dir (str): The path to the test root directory.
 
         Returns:
             Experiment: An Experiment object created from the test root directory.
@@ -852,12 +863,12 @@ def from_disk(cls, path):
             ValueError: If the path is not a valid test root directory.
         """
         from lumo.exp.watch import is_test_root
-        if not is_test_root(path):
-            raise ValueError(f'{path} is not a valid test_root')
-        path = os.path.abspath(path)
-        exp_dir = os.path.dirname(path)
+        if not is_test_root(info_dir):
+            raise ValueError(f'{info_dir} is not a valid test_root')
+        info_dir = os.path.abspath(info_dir)
+        exp_dir = os.path.dirname(info_dir)
 
-        paths_fn = os.path.join(path, 'info', f'paths.json')
+        paths_fn = os.path.join(info_dir, 'info', f'paths.json')
         if os.path.exists(paths_fn):
             try:
                 paths = io.load_json(paths_fn)
@@ -866,7 +877,7 @@ def from_disk(cls, path):
         else:
             paths = {}
 
-        self = cls(os.path.basename(exp_dir), test_name=os.path.basename(path), paths=paths)
+        self = cls(os.path.basename(exp_dir), test_name=os.path.basename(info_dir), paths=paths)
 
         # load prop
         for f in os.listdir(self.mk_ipath('info', is_dir=True)):
@@ -903,8 +914,8 @@ class SimpleExperiment(Experiment):
     execute before and after the experiment.
     """
 
-    def __init__(self, exp_name: str, root=None):
-        super().__init__(exp_name, root)
+    def __init__(self, exp_name: str = None, test_name=None, paths=None, info_dir=None):
+        super().__init__(exp_name, test_name, paths, info_dir)
         from . import exphook
         self.set_hook(exphook.LastCmd())
         self.set_hook(exphook.LockFile())
diff --git a/src/lumo/exp/exphook.py b/src/lumo/exp/exphook.py
index 2184b3e..90f2c0b 100644
--- a/src/lumo/exp/exphook.py
+++ b/src/lumo/exp/exphook.py
@@ -91,13 +91,11 @@ def exc_end(self, exc_type, exc_val, exc_tb):
         res = [i for i in res if 'in _newfunc' not in i]
 
         self.exp.dump_info('exception', {
-            'exception_type': traceback.format_exception_only(exc_type, exc_val)[-1].strip(),
+            'exception_type': exc_type.__name__,
             'exception_content': "".join(res)
         })
 
-        self.exp.end(
-            end_code=1
-        )
+        self.exp.end(end_code=1)
 
 
 # class TimeMonitor(ExpHook):
diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index 819978e..1af7398 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -1,7 +1,9 @@
 try:
     import panel as pn
 except ImportError as e:
-    raise ImportError('') from e
+    raise ImportError('The experiment panel is supported by panel, '
+                      'you should use it by `pip install panel` first.') from e
+
 from typing import Any
 
 from bokeh.core.property.primitive import String
@@ -66,21 +68,16 @@ class ExceptionFormatter:
 </details>"""
 
 
-long_text = HTMLTemplateFormatter(template=
-                                  """
-                     <details
-                        style = "overflow: visible;" >
-                     <summary > < % value['exception_type'] % > < / summary >
-                     < p
-                     style = 'display: inherit;white-space: break-spaces;word-wrap: normal;word-break: break-all;' >
-                     < %-  exception_content % >
-                     < / p >
-                     < / details >
-                     """)
+progress_formatter = HTMLTemplateFormatter(
+    template="""
+    <div style="min-height: 1.5em; width: <%-  value.ratio %>; background-color: <%-  value.color %>;" ></div>
+    """
+)
 
 tabulator_formatters = {
     'metrics': DictFormatter(column_name='metrics'),
-    'progress': DictFormatter(column_name='progress'),
+    'progress_': DictFormatter(column_name='progress'),
+    'progress': progress_formatter,
     'params': DictFormatter(column_name='params'),
     'exception': HTMLTemplateFormatter(template=ExceptionFormatter.base_template),
 }
@@ -91,10 +88,9 @@ class ExceptionFormatter:
     'params': None,
     'metrics': None,
     'progress': None,
+    'progress_': None,
     'exception': None,
     'str': {'type': 'list', 'valuesLookup': True},
-    # 'note': TextEditor(),
-    # 'tags': StringEditor(),
 }
 
 
@@ -119,9 +115,34 @@ def make_experiment_tabular(df: pd.DataFrame, reload_fn):
     else:
         df['exception'].fillna({})
 
-    # process progress
-    ratio = df['progress'].apply(lambda x: x.get('ratio', 0))
-    end_code = df['progress'].apply(lambda x: x.get('end_code', None))
+    def reformat_progress(dic):
+        ratio = dic.get('ratio', 0)
+        end_code = dic.get('end_code', None)
+
+        # normal end ->  end_code == 0 -> green
+        # interrupt by exception ->  end_code > 0 -> red
+        # running -> end_code is None -> blue
+        # killed without any signal ( in 5 minute ) ->  end_code is None -> blue
+        # killed and dumped by watcher ->  end_code == -10 -> red
+
+        if end_code is None:
+            color = 'blue'
+        elif ratio == 1:
+            color = 'green'
+        elif end_code == 0:
+            color = 'green'
+        elif end_code > 0:
+            color = 'red'
+            if ratio == 0:
+                ratio = 0.01
+
+        return {
+            'ratio': f'{ratio:2%}',
+            'color': color,
+        }
+
+    df['progress_'] = df['progress']
+    df['progress'] = df['progress'].apply(reformat_progress)
 
     # ratio = 1
     # ratio < 1, no-end-code ->
@@ -158,6 +179,7 @@ def on_cell_change(e: TableEditEvent):
         show_index=False,
         configuration={
             'clipboard': True,
+            'tooltip': True,
             # 'rowHeight': 100,
             # 'columnDefaults': {
             #     'headerSort': False,
diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index fe88874..6465b89 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -133,7 +133,7 @@ def __lt__(self, other):
         return self
 
     def __repr__(self):
-        return f'C({self.name} {self.op} {self.value})'
+        return f'C({self.name}, {self.value}, {self.op})'
 
     def in_(self, lis):
         """
@@ -239,7 +239,8 @@ def update(self):
                         updates.setdefault(exp.exp_name, []).append(exp.cache())
                     except KeyboardInterrupt as e:
                         raise e
-                    except:
+                    except Exception as e:
+                        print(e)
                         continue
                     finally:
                         os.remove(hb_file)
@@ -304,9 +305,6 @@ def progress(self, with_pandas=True):
         """
         Returns a DataFrame of alive experiments.
 
-        Args:
-            is_alive (bool): A boolean flag indicating whether to return only alive experiments.
-
         Returns:
             A pandas DataFrame containing the experiment information of alive experiments.
         """
@@ -322,14 +320,14 @@ def progress(self, with_pandas=True):
 
                     if exp.is_alive:
                         res.append(exp.dict())
-                    elif exp.properties['progress'].get('finished', None) is None:
+                    elif exp.properties['progress'].get('end_code', None) is None:
                         if (datetime.timestamp(datetime.now()) - os.stat(pid_f).st_mtime) < glob.get(
-                                'ALIVE_SECONDS', 1800):
+                                'ALIVE_SECONDS', 60 * 5):  # powered by exp/agent.py
                             res.append(exp.dict())
                     else:
                         exp.dump_info('progress',
                                       {
-                                          'end': strftime(), 'finished': True, 'end_code': -10,
+                                          'end': strftime(), 'end_code': -10,
                                           'msg': 'ended by watcher'}
                                       )
                         os.remove(pid_f)
@@ -349,175 +347,10 @@ def server(self):
         """simple server which make you note your experiments"""
         pass
 
-    def widget(self,
-               is_finished: bool = None,
-               is_alive: bool = None,
-               time_filter: list = None,
-               params_filter: list = None,
-               metric_filter: list = None
-               ):
-        """Create a user interface in jupyter with ipywidget"""
-        assert params_filter is None or isinstance(params_filter, list)
-        assert metric_filter is None or isinstance(metric_filter, list)
-
-        from ipywidgets import widgets, interact
-        from IPython.display import display
-
-        def make_row(dic: dict):
-            """
-            Helper function for creating a row in the widgets grid.
-
-            Args:
-                dic (dict): The dictionary containing the experiment information.
-
-            Returns:
-                A list of ipywidgets objects for the row.
-            """
-            exp = Experiment.from_cache(dic.copy())
-
-            def on_note_update(sender):
-                """when note textarea update"""
-                exp.dump_note(sender['new'])
-
-            def on_tag_update(sender):
-                """when tag component update"""
-                exp.dump_tags(*sender['new'])
-
-            note_ui = widgets.Textarea(dic['note'])
-
-            note_ui.continuous_update = False
-            note_ui.observe(on_note_update, names='value', type='change')
-
-            tags = dic.get('tags', [])
-            try:
-                tags = list(tags)
-            except:
-                tags = []
-            tag_ui = widgets.TagsInput(value=tags)
-            tag_ui.observe(on_tag_update, names='value', type='change')
-
-            now = datetime.now(timezone())
-            start = strptime(datestr=dic['progress']['start'])
-            end = strptime(datestr=dic['progress']['last_edit_time'])
-
-            human = widgets.VBox([
-
-            ])
-            return [
-                widgets.Label(dic['exp_name']),
-                widgets.Label(dic['test_name']),
-                widgets.Label(f"""{strftime('%y-%m-%d %H:%M:%S', dateobj=start)}"""),
-                widgets.Label(f"""{strftime('%y-%m-%d %H:%M:%S', dateobj=end)}"""),
-                widgets.HTML('\n'.join([
-                    f'{k}: {v}'
-                    for k, v in dic['metrics'].items()
-                    if isinstance(v, numbers.Number)
-                ])),
-                widgets.HBox([note_ui,
-                              tag_ui, ])
-
-            ]
-
-        test_status = widgets.RadioButtons(options=['full', 'running', 'failed', 'succeed', 'finished'])
-        start_filter = widgets.DatetimePicker()
-        end_filter = widgets.DatetimePicker()
-
-        def status_filter(sender):
-            """when filter condition changed"""
-            print(sender)
-            make()
-
-        test_status.observe(status_filter, names='value', type='change')
-
-        # display()
-
-        @interact
-        def make(
-                status=widgets.RadioButtons(options=['full', 'running', 'failed', 'succeed', 'finished']),
-                start=widgets.DatetimePicker(),
-                end=widgets.DatetimePicker(),
-        ):
-            """make widgets with filter condition."""
-            if status == 'running':
-                df = self.progress()
-            elif status == 'finished':
-                df = self.progress(is_alive=False)
-            else:
-                df = self.load()
-                if status == 'succeed':
-                    df = df[df['progress'].apply(lambda x: x['finished'])]
-                elif status == 'failed':
-                    df = df[df['exception'].isna() == False]
-
-            if start:
-                df = df.pipe(
-                    lambda x: x[x['progress'].apply(lambda y: strptime(datestr=y['start'])) > start]
-                )
-            if end:
-                df = df.pipe(
-                    lambda x: x[x['progress'].apply(lambda y: strptime(datestr=y['end'])) < end]
-                )
-
-            if params_filter is not None:
-                df_params = df['params']
-                masks = None
-                for condition in params_filter:
-                    mask = condition.mask(df_params)
-                    if masks is None:
-                        masks = mask
-                    else:
-                        masks *= mask
-                df = df[masks]
-
-            if metric_filter is not None:
-                df_params = df['metrics']
-                masks = None
-                for condition in metric_filter:
-                    mask = condition.mask(df_params)
-                    if masks is None:
-                        masks = mask
-                    else:
-                        masks *= mask
-                df = df[masks]
-
-            exps = df.to_dict(orient='records')
-            # grid = widgets.GridspecLayout(len(exps) + 1, 7)
-
-            children = [
-                widgets.Label('exp_name'),
-                widgets.Label('test_name'),
-                widgets.Label('start'),
-                widgets.Label('end'),
-                widgets.Label('metrics'),
-                widgets.Label('note & tags'),
-            ]
-            # grid[0, 0] = widgets.Label('Meta')
-            # grid[0, 1] = widgets.Label('Metrics')
-            # grid[0, 2] = widgets.Label('Notes')
-            for i, exp in enumerate(exps, start=1):
-                row = make_row(exp)
-                children.extend(row)
-                # display(widgets.HBox(row))
-                # for j, item in enumerate(row):
-                #     grid[i, j] = item
-
-            grid = widgets.GridBox(children=children,
-
-                                   layout=widgets.Layout(
-                                       width='100%',
-                                       grid_template_columns=' '.join(['auto'] * 5) + ' auto',
-                                       # grid_template_rows='80px auto 80px',
-                                       grid_gap='5px 10px')
-                                   )
-            display(
-                widgets.HTML("""
-                <style>
-                .widget-gridbox div:nth-of-type(even) {background-color: #f2f2f2 !important;}
-                </style>
-                """),
-                grid,
-
-            )
+    def panel(self):
+        from .lazy_panel import make_experiment_tabular
+        widget = make_experiment_tabular(self.load(), self.load)
+        return widget.servable()
 
 
 def is_test_root(path: str) -> bool:

From a6c388da0ac5ef842d68ef444066799e668ffb8b Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 14:59:45 +0800
Subject: [PATCH 33/95] Refine code

---
 src/lumo/trainer/components.py |  1 -
 src/lumo/trainer/trainer.py    | 38 +++++++++++++++++++++-------------
 2 files changed, 24 insertions(+), 15 deletions(-)

diff --git a/src/lumo/trainer/components.py b/src/lumo/trainer/components.py
index 37d5bf7..30dc078 100644
--- a/src/lumo/trainer/components.py
+++ b/src/lumo/trainer/components.py
@@ -15,7 +15,6 @@ def log_dir(self):
     @property
     def params_fn(self):
         res = self.mk_ipath('params.yaml')
-        self.dump_string('params.yaml', res)
         return res
 
     @property
diff --git a/src/lumo/trainer/trainer.py b/src/lumo/trainer/trainer.py
index 98ee368..87bf43b 100644
--- a/src/lumo/trainer/trainer.py
+++ b/src/lumo/trainer/trainer.py
@@ -4,6 +4,7 @@
 import warnings
 from datetime import datetime
 from functools import lru_cache
+from pprint import pformat
 from typing import Union, Dict, Any, Optional, Sequence, Mapping, Callable
 
 import numpy as np
@@ -32,7 +33,7 @@
 # overwrite send_to_device to resolve https://github.com/pytorch/pytorch/issues/83015
 # from accelerate import Accelerator
 # from accelerate.utils import send_to_device
-from ..utils.fmt import strftime
+from ..utils.fmt import strftime, indent_print
 
 ParamsType = TrainerParams
 
@@ -86,14 +87,13 @@ def __init__(self, params: ParamsType, dm: DataModule = None):
         self._saver = None
 
         self.params.iparams()
-        self.exp = TrainerExperiment(self.generate_exp_name())
+        self.exp = TrainerExperiment(exp_name=self.generate_exp_name())
 
         self._database = TableRow(self.exp.mk_ipath('metric.pkl'), persistent=self.is_main)
         self.metric_board = Metrics(self.exp.mk_bpath('board.sqlite'), persistent=self.is_main)
         self.metric = self.exp.metric
 
-        self.exp.dump_info('metric_board', self.metric_board.fpath)
-        self.exp.dump_info('table_row', self._database.fpath)
+        # self.exp.dump_info('table_row', self._database.fpath)
         self.rnd = RndManager()
 
         self.train_epoch_toggle = False
@@ -110,6 +110,14 @@ def __init__(self, params: ParamsType, dm: DataModule = None):
 
         if dist.is_main():
             self.params.to_yaml(self.exp.params_fn)
+            params_hash = self.params.hash()
+            self.exp.dump_info('trainer', {
+                'params_meta': {
+                    'fn': self.exp.params_fn,
+                    'hash': params_hash
+                },
+                'board_fn': self.metric_board.fpath
+            }, append=True)
             self.exp.dump_info('params', self.params.to_dict())
 
         self.set_global_steps(0)
@@ -170,7 +178,9 @@ def logger(self):
                 self._logger.debug('Enable debug log.')
             if self.is_main:
                 fn = self._logger.add_log_dir(self.exp.log_dir)
-                self.exp.dump_info('logger_args', {'log_dir': fn})
+                self.exp.dump_info('trainer', {
+                    'logger_fn': fn
+                }, append=True)
 
         return self._logger
 
@@ -517,10 +527,10 @@ def to_device(self, item: Optional[Union[nn.Module, torch.Tensor, Sequence, Mapp
 
     def on_trainer_exception(self, func: Callable, exception: BaseException):
         """Updates database with error information when an exception occurs during training."""
-        self.exp.dump_info('exception', dict(end=strftime(),
-                                             finished=False,
-                                             error=str(exception),
-                                             trainer_frame=str(func)))
+        # self.exp.dump_info('exception', dict(end=strftime(),
+        #                                      finished=False,
+        #                                      error=str(exception),
+        #                                      trainer_frame=str(func)), append=True)
 
     @property
     def is_initialized(self):
@@ -542,15 +552,15 @@ def initialize(self):
             return
         self.exp.start()
 
-        params_hash = self.params.hash()
-        self.exp.dump_string('params_hash', params_hash)
-
         self.icallbacks(self.params)
         self.set_property('initial.callbacks', True)
         self.imodels(self.params)
         self.set_property('initial.model', True)
         self.set_property('initial', True)
 
+        self.logger.info('Use Experiment')
+        self.logger.info(self.exp)
+
     def stop_train(self):
         """Toggle to stop train."""
         self.train_toggle = True
@@ -613,7 +623,6 @@ def train(self, dm: Union[DataModule, DataLoaderType] = None, params: ParamsType
 
         for eidx in range(params.epoch):
             # update training progress
-            self.exp.dump_train_eidx(eidx, params.epoch)
             self.set_epoch_idx(eidx)
 
             # train loop
@@ -632,7 +641,8 @@ def train(self, dm: Union[DataModule, DataLoaderType] = None, params: ParamsType
                 self.set_property('early_stop', f'meet limit_global_steps {limit_global_steps}')
                 break
 
-        # update when train finished
+            self.exp.dump_train_eidx(eidx, params.epoch)
+
         self.exp.end()
         return self._prop
 

From 5c969105e5f94d6ab3f7a760b52e728628db5963 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 14:59:56 +0800
Subject: [PATCH 34/95] wraps

---
 src/lumo/decorators/process.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/lumo/decorators/process.py b/src/lumo/decorators/process.py
index 5a48812..0e1f7dc 100644
--- a/src/lumo/decorators/process.py
+++ b/src/lumo/decorators/process.py
@@ -1,5 +1,5 @@
 from typing import Callable
-
+from functools import wraps
 from lumo.proc.dist import is_main
 
 
@@ -18,6 +18,7 @@ def call_on_main_process_wrap(func) -> Callable:
 
     """
 
+    @wraps(func)
     def inner(*args, **kwargs):
         if is_main():
             return func(*args, **kwargs)

From 45d219140139ac0681e5fc59c6243248e4156cd4 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 15:00:11 +0800
Subject: [PATCH 35/95] __repr__ to __str__ for pythonic

---
 src/lumo/data/builder.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lumo/data/builder.py b/src/lumo/data/builder.py
index 1522bc6..9f87243 100644
--- a/src/lumo/data/builder.py
+++ b/src/lumo/data/builder.py
@@ -117,7 +117,7 @@ def __init__(self):
 
         self._iter_cache = {}
 
-    def __repr__(self):
+    def __str__(self):
 
         if self.sized:
             return f'Builder(flow={pformat(self._outs)}, sized={self.sized}, size={len(self)}, iterable={self.iterable})'

From 0ed78eb6359db4650135f0334ef37ab2dd1595ef Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 15:37:33 +0800
Subject: [PATCH 36/95] Panel

---
 src/lumo/exp/experiment.py | 11 +++++------
 src/lumo/exp/lazy_panel.py | 22 +++++++++++++++++++++-
 src/lumo/exp/watch.py      |  2 +-
 3 files changed, 27 insertions(+), 8 deletions(-)

diff --git a/src/lumo/exp/experiment.py b/src/lumo/exp/experiment.py
index 203e08b..6367358 100644
--- a/src/lumo/exp/experiment.py
+++ b/src/lumo/exp/experiment.py
@@ -103,10 +103,6 @@ def __init__(self, exp_name: str = None, test_name=None, paths=None, info_dir=No
         Raises:
             ValueError: If the experiment name is not a legal filename.
         """
-        if not can_be_filename(exp_name):
-            raise ValueError(f'Experiment name should be a ligal filename(bettor only contain letter or underline),'
-                             f'but got {exp_name}.')
-
         if info_dir is not None:
             exp = self.__class__.from_disk(info_dir=info_dir)
             self._prop = exp._prop
@@ -114,6 +110,9 @@ def __init__(self, exp_name: str = None, test_name=None, paths=None, info_dir=No
             self._metric = exp._metric
         else:
             assert exp_name is not None
+            if not can_be_filename(exp_name):
+                raise ValueError(f'Experiment name should be a ligal filename(bettor only contain letter or underline),'
+                                 f'but got {exp_name}.')
             self._prop = {'exp_name': exp_name}
             if test_name is None:
                 test_name = os.environ.get(Experiment.ENV_TEST_NAME_KEY, None)
@@ -191,7 +190,7 @@ def __repr__(self):
         Returns:
             str: A string representation of the Experiment object.
         """
-        return f'{self.__class__.__name__}(info_dir={self.info_dir})'
+        return f'{self.__class__.__name__}(info_dir="{self.info_dir})"'
 
     def __str__(self):
         """
@@ -744,7 +743,7 @@ def initial(self):
             'obj': runtime_pid_obj(),
         })
 
-        self.dump_tags([])
+        self.dump_tags()
 
         # register start
         self.dump_info('progress', {'start': strftime()}, append=True)
diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index 1af7398..967bb6b 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -28,7 +28,7 @@
   min-height: 20px;
 }
 .bk {
-
+ 
 }
 .tabulator .tabulator-col-resize-handle {
  height: fit-content !important;
@@ -157,6 +157,7 @@ def reformat_progress(dic):
 
     def on_cell_change(e: TableEditEvent):
         nonlocal df
+
         if e.column == 'note':
             Experiment.from_cache(df.iloc[e.row].to_dict()).dump_note(e.value)
         else:
@@ -187,5 +188,24 @@ def on_cell_change(e: TableEditEvent):
         }
     )
 
+    # def on_cell_click(e):
+    #     nonlocal enable_update
+    #     if e.column in {'note', 'tags'}:
+    #         enable_update = False
+
+    # enable_update = True
+    # df_widget.on_click(on_cell_click)
     df_widget.on_edit(on_cell_change)
+    #
+    # def update_time():
+    #     if enable_update:
+    #         time_now = dt.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    #         time_component.object = f"<p>{time_now}</p>"
+    #
+    # time_component = pn.pane.HTML("current time is")
+    # pn.state.onload(update_time)
+    # pn.state.add_periodic_callback(update_time, 1000)  # 每1000毫秒执行一次更新时间的操作
+    #
+    # widget = pn.Column(time_component, df_widget)  # .servable()
+
     return df_widget
diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index 6465b89..75f2b5a 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -350,7 +350,7 @@ def server(self):
     def panel(self):
         from .lazy_panel import make_experiment_tabular
         widget = make_experiment_tabular(self.load(), self.load)
-        return widget.servable()
+        return widget
 
 
 def is_test_root(path: str) -> bool:

From 3881c75e8332a440534ac7e848da84947c1c4cb9 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 15:41:36 +0800
Subject: [PATCH 37/95] change css

---
 src/lumo/exp/lazy_panel.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index 967bb6b..e33c400 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -28,7 +28,7 @@
   min-height: 20px;
 }
 .bk {
- 
+ height: fit-content !important;
 }
 .tabulator .tabulator-col-resize-handle {
  height: fit-content !important;

From eeac87f7b3b6b48c5937a4fc045db444072922ef Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 15:58:30 +0800
Subject: [PATCH 38/95] Version fix

---
 src/lumo/exp/lazy_panel.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index e33c400..741803e 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -114,6 +114,8 @@ def make_experiment_tabular(df: pd.DataFrame, reload_fn):
         df['exception'] = {}
     else:
         df['exception'].fillna({})
+    if 'tags' not in df.columns:
+        df['tags'] = []
 
     def reformat_progress(dic):
         ratio = dic.get('ratio', 0)

From 24a83949093fa708f2ce7c384d046b31a993a1df Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 16:02:43 +0800
Subject: [PATCH 39/95] Version fix

---
 src/lumo/exp/lazy_panel.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index 741803e..eab81e4 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -115,7 +115,7 @@ def make_experiment_tabular(df: pd.DataFrame, reload_fn):
     else:
         df['exception'].fillna({})
     if 'tags' not in df.columns:
-        df['tags'] = []
+        df['tags'] = np.empty((len(df.index), 0)).tolist()
 
     def reformat_progress(dic):
         ratio = dic.get('ratio', 0)

From 9ccd0635d80c54b3d90db99f921fc3cb26f0df14 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 16:06:30 +0800
Subject: [PATCH 40/95] Version fix

---
 src/lumo/exp/watch.py | 25 +++++++++++++++++++++++++
 1 file changed, 25 insertions(+)

diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index 75f2b5a..b0dfd73 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -253,6 +253,31 @@ def update(self):
             dic.flush()
         return updates
 
+    def fullupdate(self):
+        updates = {}
+        for root, dirs, fs in os.walk(self.exp_root):
+            for f in dirs:
+                if is_test_name(f):
+                    info_dir = os.path.join(root, f)
+                    try:
+                        exp = Experiment.from_disk(info_dir)
+                        updates.setdefault(exp.exp_name, []).append(exp.cache())
+                    except KeyboardInterrupt as e:
+                        raise e
+                    except Exception as e:
+                        print(e)
+                        continue
+
+        for exp_name, tests in updates.items():
+            dic = PDict(os.path.join(self.db_root, f'{exp_name}.sqlite'))
+            dic.clear()
+
+            for test in tests:
+                dic[test['test_name']] = test
+            dic.flush()
+
+        return updates
+
     def load(self, with_pandas=True):
         """
         Loads the experiment information from heartbeat files and the experiment databases.

From e23460ff5472d8e75fc276faa41e6e7f31d249d0 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 16:08:01 +0800
Subject: [PATCH 41/95] Version fix

---
 src/lumo/exp/watch.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index b0dfd73..c885ff7 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -204,7 +204,7 @@ class Watcher:
 
     def __init__(self, exp_root=None, hb_root=None, pid_root=None, db_root=None):
         if exp_root is None:
-            exp_root = os.path.join(exproot(), 'hb')
+            exp_root = exproot()
 
         if hb_root is None:
             hb_root = os.path.join(cache_dir(), 'heartbeat')

From 9b9032b460b5e1a52c560ff13e1991f65376cc87 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 16:33:20 +0800
Subject: [PATCH 42/95] Version fix

---
 src/lumo/exp/lazy_panel.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index eab81e4..60faca4 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -118,6 +118,12 @@ def make_experiment_tabular(df: pd.DataFrame, reload_fn):
         df['tags'] = np.empty((len(df.index), 0)).tolist()
 
     def reformat_progress(dic):
+        if not isinstance(dic, dict):
+            return {
+                'ratio': '100%',
+                'color': 'yellow',
+            }
+
         ratio = dic.get('ratio', 0)
         end_code = dic.get('end_code', None)
 

From a04981d64c3aa93c546746c0a81ec119848ec846 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 16:38:29 +0800
Subject: [PATCH 43/95] Version fix

---
 src/lumo/exp/lazy_panel.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index 60faca4..ced0942 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -26,10 +26,13 @@
   overflow: visible !important;
   vertical-align: top;
   min-height: 20px;
+  height: fit-content !important;
 }
+
 .bk {
  height: fit-content !important;
 }
+
 .tabulator .tabulator-col-resize-handle {
  height: fit-content !important;
 

From d1c588dee010db00712333f50830561633047c65 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 16:42:39 +0800
Subject: [PATCH 44/95] Version fix

---
 src/lumo/exp/lazy_panel.py |  5 +----
 src/lumo/exp/watch.py      | 10 ++++------
 2 files changed, 5 insertions(+), 10 deletions(-)

diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index ced0942..cca8289 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -97,7 +97,7 @@ class ExceptionFormatter:
 }
 
 
-def make_experiment_tabular(df: pd.DataFrame, reload_fn):
+def make_experiment_tabular(df: pd.DataFrame):
     """
     {'start': '23-03-14-224651',
      'finished': False,
@@ -107,7 +107,6 @@ def make_experiment_tabular(df: pd.DataFrame, reload_fn):
 
     Args:
         df:
-        reload_fn:
 
     Returns:
 
@@ -175,8 +174,6 @@ def on_cell_change(e: TableEditEvent):
             tags = [i.strip() for i in e.value.split(',')]
             Experiment.from_cache(df.iloc[e.row].to_dict()).dump_tags(tags)
 
-        df = reload_fn()
-
     df_widget = pn.widgets.Tabulator(
         df,
         groupby=['exp_name'],
diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index c885ff7..24af30d 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -364,17 +364,15 @@ def progress(self, with_pandas=True):
         else:
             return res
 
-    def interactive(self):
-        """interactive, mark, label, note in ipython environment."""
-        pass
-
     def server(self):
         """simple server which make you note your experiments"""
         pass
 
-    def panel(self):
+    def panel(self, df=None):
         from .lazy_panel import make_experiment_tabular
-        widget = make_experiment_tabular(self.load(), self.load)
+        if df is None:
+            df = self.load()
+        widget = make_experiment_tabular(df)
         return widget
 
 

From 2ad758462173217e9eaf69231a2dd553f871f529 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 16:46:12 +0800
Subject: [PATCH 45/95] Enable extra columns

---
 src/lumo/exp/lazy_panel.py | 17 +++++++++++------
 1 file changed, 11 insertions(+), 6 deletions(-)

diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index cca8289..93cef5c 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -157,13 +157,21 @@ def reformat_progress(dic):
     # ratio = 1
     # ratio < 1, no-end-code ->
 
-    df = df[[
+    columns = set(df.columns) - {'git', 'paths', 'pinfo',
+                                 'execute', 'lock', 'params.yaml',
+                                 'params_hash', 'table_row', 'hooks', 'logger_args',
+                                 'metric_board'}
+    top_columns = [
         'exp_name', 'test_name',
         'progress',
         'exception',
         'params', 'metrics',
         'note', 'tags',
-    ]]
+    ]
+
+    columns = columns - set(top_columns)
+
+    df = df[top_columns + list(columns)]
 
     def on_cell_change(e: TableEditEvent):
         nonlocal df
@@ -177,10 +185,7 @@ def on_cell_change(e: TableEditEvent):
     df_widget = pn.widgets.Tabulator(
         df,
         groupby=['exp_name'],
-        hidden_columns=['git', 'paths', 'pinfo',
-                        'execute', 'lock', 'params.yaml',
-                        'params_hash', 'table_row', 'hooks', 'logger_args',
-                        'metric_board'],
+        # hidden_columns=[],
         pagination='local',
         formatters=tabulator_formatters,
         editors=tabulator_editors,

From b09268592b6985e19993140c00b2d6ee3d2a6daf Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 16:49:41 +0800
Subject: [PATCH 46/95] Enable extra columns

---
 src/lumo/exp/lazy_panel.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index 93cef5c..c16ada1 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -151,7 +151,7 @@ def reformat_progress(dic):
             'color': color,
         }
 
-    df['progress_'] = df['progress']
+    # df['progress_'] = df['progress']
     df['progress'] = df['progress'].apply(reformat_progress)
 
     # ratio = 1
@@ -160,6 +160,7 @@ def reformat_progress(dic):
     columns = set(df.columns) - {'git', 'paths', 'pinfo',
                                  'execute', 'lock', 'params.yaml',
                                  'params_hash', 'table_row', 'hooks', 'logger_args',
+                                 'agent', 'trainer', 'progress_',
                                  'metric_board'}
     top_columns = [
         'exp_name', 'test_name',

From 8995e707e7ddeb0dc19dde5e30ee6b529f8a7526 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 16:50:38 +0800
Subject: [PATCH 47/95] Copy mode in panel

---
 src/lumo/exp/lazy_panel.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index c16ada1..f223d0d 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -111,6 +111,7 @@ def make_experiment_tabular(df: pd.DataFrame):
     Returns:
 
     """
+    df = df.reset_index(drop=True)
     # process exception
     if 'exception' not in df.columns:
         df['exception'] = {}

From 018d12414f479c67242944d15c34bc66a57baec2 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 20:06:26 +0800
Subject: [PATCH 48/95] Boundcheck

---
 src/lumo/exp/lazy_panel.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index f223d0d..aeca0d9 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -142,7 +142,7 @@ def reformat_progress(dic):
             color = 'green'
         elif end_code == 0:
             color = 'green'
-        elif end_code > 0:
+        elif end_code > 0 or end_code < 0:
             color = 'red'
             if ratio == 0:
                 ratio = 0.01

From 012aa47d7fd58cfa2b887aa60768fd69f5312345 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 20:06:37 +0800
Subject: [PATCH 49/95] Add example to use Condition

---
 src/lumo/exp/watch.py | 111 ++++++++++++++++++++++++++++++++++++++++--
 1 file changed, 107 insertions(+), 4 deletions(-)

diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index 24af30d..727c6f3 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -78,7 +78,52 @@ def not_in_(ser, value):
 
 
 class Condition:
-    """Represents a condition to filter data based on a certain criteria."""
+    """
+    Represents a condition to filter data based on a certain criteria.
+
+    row filter:
+    ```
+    from lumo import C
+    import pandas as pd
+
+    # create a sample DataFrame
+    data = {'name': ['Alice', 'Bob', 'Charlie', 'David', 'Emily'],
+            'age': [25, 30, 35, 40, 45],
+            'city': ['New York', 'Los Angeles', 'Chicago', 'Houston', 'Miami']}
+    df = pd.DataFrame(data)
+
+    # create and apply the condition to filter the DataFrame
+    filtered_df = (C['age'] >= 35).apply(df)
+
+    # print the filtered DataFrame
+    print(filtered_df)
+    ```
+
+    column edit:
+    ```
+    (C+{'city.index':'cindex'}).apply(df).columns
+    # Index(['name', 'age', 'city', 'cindex'], dtype='object')
+
+    (-C['city']).apply(df).columns
+    # Index(['name', 'age'], dtype='object')
+
+    (C-['city']).apply(df).columns
+    (C-'city').apply(df).columns
+    # Index(['name', 'age'], dtype='object')
+
+    (C-['city','name']).apply(df).columns
+    # Index(['age'], dtype='object')
+    ```
+
+    pipeline:
+    ```
+    C.pipe(df,[
+        (C['age']>35),
+        C+{'city.index':'cindex'},
+        C-['city','name']
+    ])
+    ```
+    """
 
     def __init__(self, name: str = None, value=None, op=None):
         self.name = name
@@ -91,8 +136,32 @@ def __getattr__(self, item):
     def __getitem__(self, item):
         return Condition(item)
 
+    def __add__(self, other):
+        self.op = 'add_column'
+        self.value = {}
+        self.op
+        if isinstance(other, str):
+            self.value[other] = other
+        elif isinstance(other, dict):
+            self.value.update(other)
+        else:
+            raise NotImplementedError()
+        return self
+
+    def __sub__(self, other):
+        self.name = None
+        self.op = 'drop_column'
+        self.value = {}
+        if isinstance(other, str):
+            self.value.update({other: None})
+        elif isinstance(other, (list, set, dict)):
+            self.value.update({k: None for k in other})
+        else:
+            raise NotImplementedError()
+        return self
+
     def __neg__(self):
-        self.drop = True
+        self.op = 'drop_column'
         return self
 
     def __ge__(self, other):
@@ -180,12 +249,46 @@ def mask(self, df):
             if isinstance(value, pd.DataFrame):
                 value = value[i]
             else:
-                value = df.apply(lambda x: x[i])
+                value = value.apply(lambda x: x[i])
         return mapping[self.op](value, self.value)
 
+    def capply(self, df):
+        import pandas as pd
+        df = df.reset_index(drop=True)
+        if self.op == 'drop_column':
+            if isinstance(self.name, str):
+                var = [self.name]
+            elif isinstance(self.value, str):
+                var = [self.value]
+            else:
+                var = list(self.value)
+            df = df.drop(var, axis=1)
+        else:
+            assert isinstance(self.value, dict)
+            for name, aim in self.value.items():
+                names = name.split('.')
+                value = df
+                for i in names:
+                    if isinstance(value, pd.DataFrame):
+                        value = value[i]
+                    else:
+                        value = value.apply(lambda x: x[i])
+                df[aim] = value
+        return df
+
     def apply(self, df):
         """Returns a new DataFrame with only the rows that meet the condition."""
-        return df[self.mask(df)]
+        if not self.op.endswith('column'):
+            return df[self.mask(df)].reset_index(drop=True)
+        else:
+            return self.capply(df)
+
+    def pipe(self, df, conditions: List['Condition']):
+        """Applies a list of conditions to a DataFrame using the pipe method."""
+        filtered_df = df
+        for condition in conditions:
+            filtered_df = condition.apply(filtered_df)  # .reset_index(drop=True)
+        return filtered_df
 
 
 C = Condition()

From 71ee67042b8ff503e987de9e9fc31bfdbb230868 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 21:10:07 +0800
Subject: [PATCH 50/95] import

---
 src/lumo/exp/__init__.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/src/lumo/exp/__init__.py b/src/lumo/exp/__init__.py
index da726c3..b6de703 100644
--- a/src/lumo/exp/__init__.py
+++ b/src/lumo/exp/__init__.py
@@ -1 +1,3 @@
 from .experiment import SimpleExperiment, Experiment
+from .watch import Watcher, C
+from .metric import Metric

From b5f7f19838f814e6fafe7c9bd2afb57a62de8afc Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 21:10:12 +0800
Subject: [PATCH 51/95] import

---
 src/lumo/__init__.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/lumo/__init__.py b/src/lumo/__init__.py
index 5893105..5dd93f3 100644
--- a/src/lumo/__init__.py
+++ b/src/lumo/__init__.py
@@ -4,8 +4,9 @@
 __version__ = "0.15.0"
 
 from .core import Params, ParamsType, MetricType, Meter, Record, TrainStage, BaseParams
+from .proc import glob
 
 from .data import DataLoader, DataModule, DatasetBuilder, LumoDataLoader, CollateBase, DataLoaderSide
-from .exp import SimpleExperiment, Experiment
+from .exp import SimpleExperiment, Experiment, Metric, Watcher, C
 from .trainer import Trainer, TrainerParams, callbacks, RndManager
 from .utils import Logger

From 0160c3c70eadc87a941d6390edc2f1f0105f1f0e Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Wed, 15 Mar 2023 21:10:20 +0800
Subject: [PATCH 52/95] Add board command

---
 src/lumo/cli/__init__.py | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/src/lumo/cli/__init__.py b/src/lumo/cli/__init__.py
index d48da03..1a213d1 100644
--- a/src/lumo/cli/__init__.py
+++ b/src/lumo/cli/__init__.py
@@ -41,7 +41,7 @@ def note(test_name, description):
     print(f"Adding note '{description}' to {test_name}")
 
 
-def server(port=8080):
+def board(port=11606, address=None, open=True):
     """
 
     Args:
@@ -50,6 +50,9 @@ def server(port=8080):
     Returns:
 
     """
+    from lumo import Watcher
+    w = Watcher()
+    w.panel().show(port=port, address=address, open=open)
     print(f"Starting server on port {port}")
 
 
@@ -57,5 +60,5 @@ def main():
     fire.Fire({
         'rerun': rerun,
         'note': note,
-        'server': server,
+        'board': board,
     })

From 2ef8c1656fea336b1baffbb87f3b34d58eea934e Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 14:19:32 +0800
Subject: [PATCH 53/95] Add one-file examples

---
 examples/imagenet.py | 253 +++++++++++++++++++++++++++++++++++++
 examples/mnist.py    | 117 ++++++++++++++++++
 examples/moco.py     | 288 +++++++++++++++++++++++++++++++++++++++++++
 3 files changed, 658 insertions(+)
 create mode 100644 examples/imagenet.py
 create mode 100644 examples/mnist.py
 create mode 100644 examples/moco.py

diff --git a/examples/imagenet.py b/examples/imagenet.py
new file mode 100644
index 0000000..4a61e57
--- /dev/null
+++ b/examples/imagenet.py
@@ -0,0 +1,253 @@
+import sys
+from pathlib import Path
+from typing import Union
+
+import torch
+from PIL import Image
+from torch.utils.data import DataLoader
+import os
+
+from torchvision.datasets.folder import default_loader
+
+from lumo import DatasetBuilder, MetricType, Trainer, TrainerParams, Meter, callbacks, DataModule
+from torchvision.datasets import FakeData, ImageFolder
+from torchvision import transforms
+from torchvision.models.resnet import resnet18
+from torch import nn
+from lumo.proc.dist import is_dist, is_main
+from torch.nn import functional as F
+from lumo.proc import glob
+from lumo.utils.subprocess import run_command
+
+"""define transforms"""
+
+
+def none(mean, std):
+    return transforms.Compose([
+        transforms.ToTensor(),
+        transforms.Normalize(mean, std)
+    ])
+
+
+def standard(mean, std, resize=None):
+    return transforms.Compose([
+        transforms.RandomResizedCrop(224),
+        transforms.RandomHorizontalFlip(),
+        transforms.ToTensor(),
+        transforms.Normalize(mean, std)
+    ])
+
+
+"""create datasets"""
+
+
+def imagenet(split='train'):
+    """
+    download from https://www.kaggle.com/c/imagenet-object-localization-challenge/overview/description
+    ```
+    mkdir imagenet
+    cd ./imagenet
+    kaggle competitions download -c imagenet-object-localization-challenge
+    unzip imagenet-object-localization-challenge.zip
+    tar -xvf imagenet_object_localization_patched2019.tar.gz
+    ls
+    >>> ILSVRC LOC_synset_mapping.txt  LOC_val_solution.csv imagenet_object_localization_patched2019.tar.gz
+    >>> LOC_sample_submission.csv  LOC_train_solution.csv  imagenet-object-localization-challenge.zip
+    ```
+    """
+    root = glob['imagenet']
+    if split == 'train':
+        file = Path(root).joinpath('ILSVRC', 'ImageSets', 'CLS-LOC', 'train_cls.txt')
+        train_root = os.path.join(root, 'ILSVRC/Data/CLS-LOC/train')
+        with file.open('r') as r:
+            lines = r.readlines()
+            imgs = [line.split(' ')[0] for line in lines]
+            name_cls_map = {name: i for i, name in enumerate(sorted(set([i.split('/')[0] for i in imgs])))}
+            xs = [os.path.join(train_root, f'{i}.JPEG') for i in imgs]
+            ys = [name_cls_map[i.split('/')[0]] for i in imgs]
+    else:
+        file = Path(root).joinpath('LOC_val_solution.csv')
+        val_root = os.path.join(root, 'ILSVRC/Data/CLS-LOC/val')
+
+        with file.open('r') as r:
+            r.readline()
+            lines = r.readlines()
+            lines = [line.split(',') for line in lines]
+            lines = [[img, res.split(' ')[0]] for img, res in lines]
+
+            name_cls_map = {name: i for i, name in enumerate(sorted(set([i[1] for i in lines])))}
+            xs = [os.path.join(val_root, f'{img}.JPEG') for img, _ in lines]
+            ys = [name_cls_map[res] for _, res in lines]
+
+    return list(xs), list(ys)
+
+
+def take_first(item):
+    return item[0]
+
+
+def take_second(item):
+    return item[1]
+
+
+def make_dataset(dummy=False):
+    if dummy:
+        train_dataset = FakeData(1281167, (3, 224, 224), 1000, transforms.ToTensor())
+        val_dataset = FakeData(50000, (3, 224, 224), 1000, transforms.ToTensor())
+        ds = (
+            DatasetBuilder()
+                .add_input('fake', train_dataset)
+                .add_output('fake', 'xs', transform=take_first)
+                .add_output('fake', 'ys', transform=take_second)
+        )
+        test_ds = (
+            DatasetBuilder()
+                .add_input('fake', val_dataset)
+                .add_output('fake', 'xs', transform=take_first)
+                .add_output('fake', 'ys', transform=take_second)
+        )
+    else:
+        train_dataset = ImageFolder(os.path.join(glob['imagenet'], 'train'))
+        val_dataset = ImageFolder(os.path.join(glob['imagenet'], 'val'))
+
+        xs, ys = list(zip(*train_dataset.samples))
+        test_xs, test_ys = list(zip(*val_dataset.samples))
+
+        mean = [0.485, 0.456, 0.406]
+        std = [0.229, 0.224, 0.225]
+
+        ds = (
+            DatasetBuilder()
+                .add_input('xs', xs, transform=default_loader)  # 注册样本来源，命名为 'xs'
+                .add_input('ys', ys)  # 注册标签来源，命名为 'ys'
+                .add_output('xs', 'xs', transform=standard(mean, std))  # 添加一个弱增广输出 'xs0'
+                .add_output('ys', 'ys')  # 添加标签输出
+        )
+
+        print(ds)
+        print(ds[0].keys())
+
+        test_ds = (
+            DatasetBuilder()
+                .add_input('xs', test_xs, transform=default_loader)  # 注册样本来源，命名为 'xs'
+                .add_input('ys', test_ys)  # 注册标签来源，命名为 'ys'
+                .add_output('xs', 'xs', transform=none(mean, std))  # 测试样本不使用增广
+                .add_output('ys', 'ys')  # 添加标签输出
+        )
+
+    print(test_ds)
+    print(test_ds[0].keys())
+    return ds, test_ds
+
+
+class LargeParams(TrainerParams):
+    def __init__(self):
+        super().__init__()
+        self.optim = self.OPTIM.create_optim('SGD',
+                                             lr=0.06,
+                                             momentum=0.9,
+                                             weight_decay=5e-5,
+                                             )
+        self.lr_decay_end = 0.00001
+        self.batch_size = 512
+        self.dummy = False
+        self.multiprocessing_distributed = True
+
+
+ParamsType = LargeParams
+
+
+class LargeModel(nn.Module):
+
+    def __init__(self, feature_dim) -> None:
+        super().__init__()
+        self.backbone = resnet18()
+        in_feature = self.backbone.fc.in_features
+        self.backbone.fc = nn.Identity()
+        self.head = nn.Linear(in_feature, feature_dim, bias=True)
+
+    def forward(self, xs):
+        feature_map = self.backbone(xs)
+        feature = self.head(feature_map)
+        return feature
+
+
+class LargeTrainer(Trainer):
+
+    def icallbacks(self, params: ParamsType):
+        callbacks.LoggerCallback().hook(self)
+
+    def imodels(self, params: ParamsType):
+        self.model = resnet18(num_classes=1000)
+        self.optim = params.optim.build(self.model.parameters())
+
+        self.lr_sche = params.SCHE.Cos(
+            start=params.optim.lr, end=params.lr_decay_end,
+            left=0,
+            right=len(self.train_dataloader) * params.epoch
+        )
+        # manually trigger send_to_device method
+        self.to_device()
+
+    def train_step(self, batch, params: ParamsType = None) -> MetricType:
+        super().train_step(batch, params)
+        m = Meter()
+        eval_xs, xs, ys = batch['xs0'], batch['xs1'], batch['ys']
+        logits = self.model(xs)
+
+        Lall = F.cross_entropy(logits, ys)
+        self.optim.zero_grad()
+        self.accelerate.backward(Lall)
+        self.optim.step()
+
+        # change lr by training epoch
+        cur_lr = self.lr_sche.apply(self.optim, self.eidx)
+
+        with torch.no_grad():
+            m.mean.Lall = Lall
+            eval_logits = self.model(eval_xs)
+            m.mean.Ax = torch.eq(eval_logits.argmax(dim=-1), ys).float().mean()
+            m.last.lr = cur_lr
+        return m
+
+    def test_step(self, batch, params: ParamsType = None) -> MetricType:
+        m = Meter()
+        xs, ys = batch['xs'], batch['ys']
+        logits = self.model(xs)
+
+        all_logits = self.accelerate.gather(logits)
+        all_ys = self.accelerate.gather(ys)
+
+        m.test_mean.Ax = torch.eq(all_logits.argmax(dim=-1), all_ys).float()
+        return m
+
+
+def main():
+    params = LargeParams()
+    params.from_args()
+
+    if params.multiprocessing_distributed and not is_dist():
+        command = ' '.join([
+            'accelerate', 'launch',
+            *sys.argv,
+        ])
+        run_command(command)
+    else:  # not distributed or in distribution environment
+        # create datamodule to contain dataloader
+        ds, test_ds = make_dataset(dummy=params.dummy)
+        dl = ds.DataLoader(batch_size=params.batch_size)
+        test_dl = test_ds.DataLoader(batch_size=params.batch_size)
+        dm = DataModule()
+        dm.regist_dataloader(train=dl, test=test_dl)
+
+        # with the input of params and dataloader, the initialization of models and optimizers in Trainer,
+        # then the output will be the trained parameters, metrics and logs.
+        trainer = LargeTrainer(params, dm=dm)
+
+        trainer.train()  # or trainer.train(dm=dl) if dm are not given above
+        trainer.test()  # or trainer.test(dm=dl)
+        trainer.save_last_model()
+
+
+if __name__ == '__main__':
+    main()
diff --git a/examples/mnist.py b/examples/mnist.py
new file mode 100644
index 0000000..45cc6a6
--- /dev/null
+++ b/examples/mnist.py
@@ -0,0 +1,117 @@
+import torch
+from lumo import DatasetBuilder, MetricType, Trainer, TrainerParams, Meter, callbacks, DataModule
+from lumo.proc.path import cache_dir
+from torchvision.datasets.mnist import MNIST
+from torchvision.transforms import Compose, RandomCrop, Normalize
+from torch import nn
+from torch.nn import functional as F
+
+
+def make_dataset():
+    data = MNIST(root=cache_dir(), train=True, download=True)
+    test_data = MNIST(root=cache_dir(), train=False, download=True)
+
+    mean = torch.mean(data.data / 255.)
+    std = torch.std(data.data / 255.)
+
+    ds = (
+        DatasetBuilder()
+            .add_input('xs', data.data.float().unsqueeze(1))  # 注册样本来源，命名为 'xs'
+            .add_input('ys', data.targets)  # 注册标签来源，命名为 'ys'
+            .add_output('xs', 'xs0', transform=Normalize(mean=(mean,), std=(std,)))  # 添加一个弱增广输出 'xs0'
+            .add_output('xs', 'xs1',
+                        transform=Compose(
+                            [RandomCrop(28, padding=4), Normalize(mean=(mean,), std=(std,))]))  # 添加一个强增广输出 'xs1'
+            .add_output('ys', 'ys')  # 添加标签输出
+    )
+    print(ds)
+    print(ds[0].keys())
+
+    test_ds = (
+        DatasetBuilder()
+            .add_input('xs', test_data.data.float().unsqueeze(1))  # 注册样本来源，命名为 'xs'
+            .add_input('ys', test_data.targets)  # 注册标签来源，命名为 'ys'
+            .add_output('xs', 'xs', transform=Normalize(mean=(mean,), std=(std,)))  # 测试样本不使用增广
+            .add_output('ys', 'ys')  # 添加标签输出
+    )
+
+    print(test_ds)
+    print(test_ds[0].keys())
+    return ds, test_ds
+
+
+class MNISTParams(TrainerParams):
+    def __init__(self):
+        super().__init__()
+        self.batch_size = 128
+        self.optim = self.OPTIM.create_optim('SGD', lr=0.0001, momentum=0.9)
+
+
+ParamsType = MNISTParams
+
+
+class MNISTTrainer(Trainer):
+
+    def icallbacks(self, params: ParamsType):
+        super().icallbacks(params)
+        callbacks.LoggerCallback().hook(self)
+
+    def imodels(self, params: ParamsType):
+        super().imodels(params)
+        self.model = nn.Sequential(
+            nn.Flatten(),
+            nn.Linear(28 * 28, 128),
+            nn.ReLU(),
+            nn.Linear(128, 10),
+        )
+        self.optim = params.optim.build(self.model.parameters())
+
+        # manually trigger send_to_device method
+        self.to_device()
+
+    def train_step(self, batch, params: ParamsType = None) -> MetricType:
+        super().train_step(batch, params)
+        m = Meter()
+        eval_xs, xs, ys = batch['xs0'], batch['xs1'], batch['ys']
+        logits = self.model(xs)
+        Lall = F.cross_entropy(logits, ys)
+        self.optim.zero_grad()
+        Lall.backward()
+        self.optim.step()
+        with torch.no_grad():
+            m.mean.Lall = Lall
+            eval_logits = self.model(eval_xs)
+            m.mean.Ax = torch.eq(eval_logits.argmax(dim=-1), ys).float().mean()
+        return m
+
+    def test_step(self, batch, params: ParamsType = None) -> MetricType:
+        m = Meter()
+        xs, ys = batch['xs'], batch['ys']
+        logits = self.model(xs)
+        m.test_mean.Ax = torch.eq(logits.argmax(dim=-1), ys).float()
+        return m
+
+
+def main():
+    ds, test_ds = make_dataset()
+
+    # create datamodule to contain dataloader
+    dl = ds.DataLoader(batch_size=32)
+    test_dl = test_ds.DataLoader(batch_size=32)
+    dm = DataModule()
+    dm.regist_dataloader(train=dl, test=test_dl)
+
+    params = MNISTParams()
+    params.epoch = 10
+    params.from_args()
+    # with the input of params and dataloader, the initialization of models and optimizers in Trainer,
+    # then the output will be the trained parameters, metrics and logs.
+    trainer = MNISTTrainer(params, dm=dm)
+
+    trainer.train()  # or trainer.train(dm=dl) if dm are not given above
+    trainer.test()  # or trainer.test(dm=dl)
+    trainer.save_last_model()
+
+
+if __name__ == '__main__':
+    main()
diff --git a/examples/moco.py b/examples/moco.py
new file mode 100644
index 0000000..f911367
--- /dev/null
+++ b/examples/moco.py
@@ -0,0 +1,288 @@
+"""
+refer to
+https://colab.research.google.com/github/facebookresearch/moco/blob/colab-notebook/colab/moco_cifar10_demo.ipynb
+"""
+from typing import Union
+
+import torch
+from PIL import Image
+from torch.utils.data import DataLoader
+
+from lumo import DatasetBuilder, MetricType, Trainer, TrainerParams, Meter, callbacks, DataModule
+from lumo.contrib import EMA, MemoryBank, StorageBank
+from lumo.contrib.accelerate.utils import send_to_device
+from lumo.contrib.nn.loss import contrastive_loss2
+from lumo.proc.path import cache_dir
+from torchvision.datasets.cifar import CIFAR10
+from torchvision import transforms
+from torchvision.models.resnet import resnet18
+from torch import nn
+from torch.nn import functional as F
+
+"""define transforms"""
+
+
+def none(mean, std):
+    return transforms.Compose([
+        transforms.ToTensor(),
+        transforms.Normalize(mean, std)
+    ])
+
+
+def simclr(mean, std):
+    return transforms.Compose([
+        transforms.RandomResizedCrop(32),
+        transforms.RandomHorizontalFlip(),
+        transforms.RandomApply([
+            transforms.ColorJitter(0.4, 0.4, 0.4, 0.1)
+        ], p=0.8),
+        transforms.RandomGrayscale(0.2),
+        transforms.ToTensor(),
+        transforms.Normalize(mean, std)
+    ])
+
+
+"""create datasets"""
+
+
+def make_dataset():
+    data = CIFAR10(root=cache_dir(), train=True, download=True)
+    data.data = [Image.fromarray(img) for img in data.data]
+    test_data = CIFAR10(root=cache_dir(), train=False, download=True)
+
+    mean = [0.4914, 0.4822, 0.4465]
+    std = [0.2023, 0.1994, 0.2010]
+
+    ds = (
+        DatasetBuilder()
+            .add_input('xs', data.data)  # 注册样本来源，命名为 'xs'
+            .add_input('ys', data.targets)  # 注册标签来源，命名为 'ys'
+            .add_output('xs', 'xs0', transform=simclr(mean, std))  # 添加一个弱增广输出 'xs0'
+            .add_output('xs', 'xs1', transform=simclr(mean, std))  # 添加一个强增广输出 'xs1'
+            .add_output('ys', 'ys')  # 添加标签输出
+    )
+
+    # for knn test
+    memo_ds = (
+        DatasetBuilder()
+            .add_input('xs', data.data)  # 注册样本来源，命名为 'xs'
+            .add_input('ys', data.targets)  # 注册标签来源，命名为 'ys'
+            .add_output('xs', 'xs', transform=none(mean, std))  # 添加一个弱增广输出 'xs0'
+            .add_output('ys', 'ys')  # 添加标签输出
+    )
+    print(ds)
+    print(ds[0].keys())
+
+    test_ds = (
+        DatasetBuilder()
+            .add_idx('idx')  # add index key for sample
+            .add_input('xs', test_data.data)  # 注册样本来源，命名为 'xs'
+            .add_input('ys', test_data.targets)  # 注册标签来源，命名为 'ys'
+            .add_output('xs', 'xs', transform=none(mean, std))  # 测试样本不使用增广
+            .add_output('ys', 'ys')  # 添加标签输出
+    )
+
+    print(test_ds)
+    print(test_ds[0].keys())
+    return ds, memo_ds, test_ds
+
+
+class MocoParams(TrainerParams):
+    def __init__(self):
+        super().__init__()
+        self.optim = self.OPTIM.create_optim('SGD',
+                                             lr=0.06,
+                                             momentum=0.9,
+                                             weight_decay=5e-5,
+                                             )
+        self.lr_decay_end = 0.00001
+        self.temperature = 0.1
+        self.ema_alpha = 0.99
+        self.feature_dim = 129
+        self.queue_size = 4096
+        self.batch_size = 512
+        self.symmetric = False
+
+
+ParamsType = MocoParams
+
+
+class MocoModel(nn.Module):
+
+    def __init__(self, feature_dim) -> None:
+        super().__init__()
+        self.backbone = resnet18()
+        in_feature = self.backbone.fc.in_features
+        self.backbone.fc = nn.Identity()
+        self.head = nn.Linear(in_feature, feature_dim, bias=True)
+
+    def forward(self, xs):
+        feature_map = self.backbone(xs)
+        feature = self.head(feature_map)
+        return feature
+
+
+def knn_predict(feature, feature_bank, feature_labels, classes, knn_k, knn_t):
+    # compute cos similarity between each feature vector and feature bank ---> [B, N]
+    sim_matrix = torch.mm(feature, feature_bank)
+    # [B, K]
+    sim_weight, sim_indices = sim_matrix.topk(k=knn_k, dim=-1)
+    # [B, K]
+    sim_labels = torch.gather(feature_labels.expand(feature.size(0), -1), dim=-1, index=sim_indices)
+    sim_weight = (sim_weight / knn_t).exp()
+
+    # counts for each class
+    one_hot_label = torch.zeros(feature.size(0) * knn_k, classes, device=sim_labels.device)
+    # [B*K, C]
+    one_hot_label = one_hot_label.scatter(dim=-1, index=sim_labels.view(-1, 1), value=1.0)
+    # weighted score ---> [B, C]
+    pred_scores = torch.sum(one_hot_label.view(feature.size(0), -1, classes) * sim_weight.unsqueeze(dim=-1), dim=1)
+
+    pred_labels = pred_scores.argsort(dim=-1, descending=True)
+    return pred_labels
+
+
+class MocoTrainer(Trainer):
+
+    def icallbacks(self, params: ParamsType):
+        callbacks.LoggerCallback().hook(self)
+
+    def imodels(self, params: ParamsType):
+        self.model = MocoModel(params.feature_dim)
+        self.ema_model = EMA(self.model, alpha=params.ema_alpha)
+
+        self.optim = params.optim.build(self.model.parameters())
+
+        self.tensors = StorageBank()
+        self.tensors.register('test_feature', dim=params.feature_dim, k=len(self.dm.test_dataset))
+        self.tensors.register('test_ys', dim=-1, k=len(self.dm.test_dataset), dtype=torch.long)
+
+        self.mem = MemoryBank()
+        # do not need normalize because normalize is applied in contrastive_loss2 function
+        self.mem.register('negative', dim=params.feature_dim, k=params.queue_size)
+        self.mem['negative'] = F.normalize(self.mem['negative'], dim=-1)
+
+        self.lr_sche = params.SCHE.Cos(
+            start=params.optim.lr, end=params.lr_decay_end,
+            left=0,
+            right=len(self.train_dataloader) * params.epoch
+        )
+        # manually trigger send_to_device method
+        self.to_device()
+
+    def train_step(self, batch, params: ParamsType = None) -> MetricType:
+        m = Meter()
+        im_query, im_key, ys = batch['xs0'], batch['xs1'], batch['ys']
+        feat_query = self.model.forward(im_query)
+
+        with torch.no_grad():
+            # shuffle for making use of BN
+            feat_key = self.ema_model.forward(im_key)  # keys: NxC
+            feat_key = F.normalize(feat_key, dim=1)  # already normalized
+
+        feat_query = F.normalize(feat_query, dim=1)
+
+        if params.symmetric:
+            Lcsa = contrastive_loss2(query=feat_query, key=feat_key,
+                                     memory=self.mem['negative'],
+                                     query_neg=False, key_neg=False,
+                                     temperature=params.temperature,
+                                     norm=False)
+            Lcsb = contrastive_loss2(query=feat_key, key=feat_query,
+                                     memory=self.mem['negative'],
+                                     query_neg=False, key_neg=False,
+                                     temperature=params.temperature,
+                                     norm=False)
+            Lcs = Lcsa + Lcsb
+        else:
+
+            Lcs = contrastive_loss2(query=feat_query, key=feat_key.detach(),
+                                    memory=self.mem['negative'].clone().detach(),
+                                    query_neg=False, key_neg=False,
+                                    temperature=params.temperature,
+                                    norm=False)
+
+            # memory bank
+        with torch.no_grad():
+            if params.symmetric:
+                self.mem.push('negative', torch.cat([feat_query, feat_key], dim=0))
+            else:
+                self.mem.push('negative', feat_key)
+
+        self.optim.zero_grad()
+        self.accelerate.backward(Lcs)
+        self.optim.step()
+        cur_lr = self.lr_sche.apply(self.optim, self.global_steps)
+
+        # metrics
+        with torch.no_grad():
+            m.mean.Lcs = Lcs
+            m.last.lr = cur_lr
+        return m
+
+    def test_step(self, batch, params: ParamsType = None) -> MetricType:
+        idx = batch['idx']
+        xs, ys = batch['xs'], batch['ys']
+        feature = self.model(xs)
+        self.tensors.scatter('test_feature', feature, idx)
+        self.tensors.scatter('test_ys', ys, idx)
+
+    def test(self, dm: Union[DataModule, DataLoader] = None, params: ParamsType = None, limit_step=None):
+        super().test(dm, params, limit_step)  # run default test loop
+        self.save_last_model()
+
+        feature_bank = []
+        with torch.no_grad():
+            # generate feature bank
+            for batch in self.dm['memo']:
+                batch = send_to_device(batch, self.device)
+                data, target = batch['xs'], batch['ys']
+                feature = self.model(data)
+                feature = F.normalize(feature, dim=1)
+                feature_bank.append(feature)
+
+            feature_bank = torch.cat(feature_bank, dim=0).t().contiguous()
+            # [N]
+            feature_labels = torch.tensor(self.dm['memo'].dataset.inputs['ys'], device=feature_bank.device)
+            # loop test data to predict the label by weighted knn search
+
+            pred_labels = knn_predict(self.tensors['test_feature'],
+                                      feature_bank, feature_labels, params.n_classes, params.knn_k, params.knn_t)
+            total_num = pred_labels.shape[0]
+            total_top1 = torch.eq(pred_labels[:, 0], self.tensors['test_ys']).float().sum().item()
+
+            knn_acc = total_top1 / total_num * 100
+
+        max_knn_acc = self.metric.dump_metric('Knn', knn_acc, cmp='max', flush=True)
+        self.logger.info(f'Best Knn Top-1 acc: {max_knn_acc}, current: {knn_acc}')
+
+        if knn_acc >= max_knn_acc:
+            self.save_best_model()
+
+
+def main():
+    ds, memo_ds, test_ds = make_dataset()
+
+    params = MocoParams()
+    params.from_args()
+
+    # create datamodule to contain dataloader
+    dl = ds.DataLoader(batch_size=params.batch_size)
+    memo_dl = memo_ds.DataLoader(batch_size=params.batch_size)
+    test_dl = test_ds.DataLoader(batch_size=params.batch_size)
+    dm = DataModule()
+    dm.regist_dataloader(train=dl,
+                         test=test_dl,
+                         memo=memo_dl)  # add extra dataloader with any name
+
+    # with the input of params and dataloader, the initialization of models and optimizers in Trainer,
+    # then the output will be the trained parameters, metrics and logs.
+    trainer = MocoTrainer(params, dm=dm)
+
+    trainer.train()  # or trainer.train(dm=dl) if dm are not given above
+    trainer.test()  # or trainer.test(dm=dl)
+    trainer.save_last_model()
+
+
+if __name__ == '__main__':
+    main()

From 7973f91050864e4acb5b7aef39d0e713ea1a373c Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 14:20:01 +0800
Subject: [PATCH 54/95] Meter: agg array

---
 src/lumo/core/meter.py | 27 ++++++++++++++++++++++++---
 1 file changed, 24 insertions(+), 3 deletions(-)

diff --git a/src/lumo/core/meter.py b/src/lumo/core/meter.py
index 44bc21b..7c52bc4 100644
--- a/src/lumo/core/meter.py
+++ b/src/lumo/core/meter.py
@@ -126,9 +126,10 @@ def __setitem__(self, key, value):
         stg = self._avg.get(key, None)
         isscalar = value.size == 1
 
-        if stg is None:
+        if stg is None:  # Auto infer a stg method for the value
             dtype = value.dtype.name
 
+            # sanity check
             if self._stage in {'min', 'max'} and not isscalar:
                 raise ValueError(
                     f'Only support min/max(a) operator on scalar metrics, but got data of shape {value.shape}.')
@@ -145,9 +146,14 @@ def __setitem__(self, key, value):
                     self._stage = 'last'
 
             self._avg[key] = self._stage
+            stg = self._stage
 
         if isscalar:
             value = value.item()
+        elif stg == {'min', 'max', 'sum'}:
+            value = getattr(np, stg)(value).item()
+        elif stg == 'mean':
+            value = [getattr(np, stg)(value).item(), value.size]
 
         self._rec[key] = value
         self._stage = 'default'
@@ -192,6 +198,17 @@ def mean(self):
         self._stage = 'mean'
         return self
 
+    @property
+    def test_mean(self):
+        """
+        Sets the aggregation method to 'mean'.
+
+        Returns:
+            The meter itself.
+        """
+        self._stage = 'mean'
+        return self
+
     @property
     def last(self):
         """
@@ -405,6 +422,10 @@ def __repr__(self):
     def update(self, item):
         """Updates the reduction value with a new item."""
         self.cur = item
+        count = 1
+        if isinstance(item, list) and len(item) == 2:
+            item, count = item
+
         item = detach(item)
 
         avg = self.gb_method
@@ -419,8 +440,8 @@ def update(self, item):
         elif avg in {'mean', 'sum'}:
             if len(self.acc) == 0:
                 self.acc.append(0)
-            self.acc[0] = self.acc[0] + item
-            self.c += 1
+            self.acc[0] = self.acc[0] + item * count
+            self.c += count
         elif avg == 'max':
             self._res = max(self.cur, self._res)
         elif avg == 'min':

From d2c1ae2f46591c7070f42f1af92ac0097d7d6fa7 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 14:20:28 +0800
Subject: [PATCH 55/95] DatasetBuilder: fix typehint of pycharm

---
 src/lumo/data/builder.py | 26 +++++++++++++-------------
 1 file changed, 13 insertions(+), 13 deletions(-)

diff --git a/src/lumo/data/builder.py b/src/lumo/data/builder.py
index 9f87243..7515aa2 100644
--- a/src/lumo/data/builder.py
+++ b/src/lumo/data/builder.py
@@ -360,7 +360,7 @@ def scale_to_size(self, size: int):
             size (int): the size to scale the dataset builder to.
 
         Returns:
-            self (DatasetBuilder): the scaled dataset builder.
+            the scaled dataset builder.
         """
         assert isinstance(size, int)
         assert 'pseudo_repeat' not in self._prop
@@ -378,7 +378,7 @@ def repeat(self, multiple: int):
             multiple (int): the number of times to repeat the dataset builder.
 
         Returns:
-            self (DatasetBuilder): the repeated dataset builder.
+            the repeated dataset builder.
         """
         assert isinstance(multiple, int)
         assert 'pseudo_length' not in self._prop
@@ -424,7 +424,7 @@ def chain(self):
         Set the mode of the dataset builder to chain.
 
         Returns:
-            self (DatasetBuilder): the dataset builder with the chain mode set.
+            the dataset builder with the chain mode set.
         """
         self._prop['mode'] = 'chain'
         return self
@@ -434,7 +434,7 @@ def item(self):
         Set the mode of the dataset builder to item.
 
         Returns:
-            self (DatasetBuilder): the dataset builder with the item mode set.
+            the dataset builder with the item mode set.
         """
         self._prop['mode'] = 'item'
         return self
@@ -444,7 +444,7 @@ def zip(self):
         Set the mode of the dataset builder to zip.
 
         Returns:
-            self (DatasetBuilder): the dataset builder with the zip mode set.
+            the dataset builder with the zip mode set.
         """
         self._prop['mode'] = 'zip'
         return self
@@ -489,7 +489,7 @@ def add_idx(self, name):
             name (str): the name of the index.
 
         Returns:
-            self (DatasetBuilder): the dataset builder with the index added.
+            the dataset builder with the index added.
         """
         outkeys = self._outs.setdefault(f"::idx::", [])
         assert name not in self._outkeys, f'Output key {name} duplicated.'
@@ -507,7 +507,7 @@ def add_input(self, name: str, source, transform: SingleValueTransform = None):
             transform (SingleValueTransform): the transform to apply to the input source.
 
         Returns:
-            self (DatasetBuilder): the dataset builder with the input source added.
+            the dataset builder with the input source added.
 
         Notes:
             Iterable object without `__len__` method currently are not well-tested. Be careful to use them in DatasetBuilder.
@@ -529,7 +529,7 @@ def add_input_transform(self, name: str, transform: SingleValueTransform = None)
             transform (SingleValueTransform): the transform to add.
 
         Returns:
-            self (DatasetBuilder): the dataset builder with the transform added.
+            the dataset builder with the transform added.
         """
         assert name in self._data, f'Source {name} should be added.'
         warnings.warn('`add` may cause confusion, use set_input_transform ')
@@ -545,7 +545,7 @@ def add_output(self, name: str, outkey: str, transform: SingleValueTransform = N
             transform (SingleValueTransform): the transform to apply to the output.
 
         Returns:
-            self (DatasetBuilder): the dataset builder with the output added.
+            the dataset builder with the output added.
         """
         assert name in self._data, f'Must have data source {name} first.'
 
@@ -567,7 +567,7 @@ def add_output_transform(self, outkey: str, transform: SingleValueTransform = No
             transform (SingleValueTransform): the transform to add.
 
         Returns:
-            self (DatasetBuilder): the dataset builder with the transform added.
+            the dataset builder with the transform added.
         """
         assert outkey in self._outkeys, f'Output key {outkey} should be added.'
         warnings.warn('add may cause confusion, use set_output_transform ')
@@ -581,7 +581,7 @@ def add_global_transform(self, transform: DictTransform):
             transform (DictTransform): the global transform to apply to the dataset.
 
         Returns:
-            self (DatasetBuilder): the dataset builder with the global transform added.
+            the dataset builder with the global transform added.
         """
         self._transforms['::global::'] = transform
         return self
@@ -595,7 +595,7 @@ def set_input_transform(self, name, transform: SingleValueTransform = None):
             transform (SingleValueTransform): the transform to set.
 
         Returns:
-            self (DatasetBuilder): the dataset builder with the transform set.
+            the dataset builder with the transform set.
         """
         self._transforms[name] = transform
         return self
@@ -609,7 +609,7 @@ def set_output_transform(self, outkey, transform: SingleValueTransform = None):
             transform (SingleValueTransform): the transform to set.
 
         Returns:
-            self (DatasetBuilder): the dataset builder with the transform set.
+            the dataset builder with the transform set.
         """
         self._transforms[f'::{outkey}'] = transform
         return self

From f13f1c3daf00cbb22706210b693c3377db6aff91 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 14:20:49 +0800
Subject: [PATCH 56/95] panel: beautify

---
 src/lumo/exp/lazy_panel.py | 124 ++++++++++++++++++++++---------------
 1 file changed, 75 insertions(+), 49 deletions(-)

diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index aeca0d9..a035bf3 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -1,20 +1,16 @@
+import numbers
+
 try:
     import panel as pn
 except ImportError as e:
     raise ImportError('The experiment panel is supported by panel, '
                       'you should use it by `pip install panel` first.') from e
 
-from typing import Any
-
-from bokeh.core.property.primitive import String
-from bokeh.plotting import figure
 import pandas as pd
 from panel.models.tabulator import TableEditEvent
 
-from lumo.exp.watch import Watcher
-import datetime as dt
 import numpy as np
-from bokeh.models.widgets.tables import HTMLTemplateFormatter, NumberFormatter, TextEditor, StringEditor
+from bokeh.models.widgets.tables import HTMLTemplateFormatter
 from lumo import Experiment
 
 css = '''
@@ -48,7 +44,7 @@
 pn.extension('tabulator', raw_css=[css], css_files=[pn.io.resources.CSS_URLS['font-awesome']])
 
 
-def DictFormatter(column_name):
+def FoldDictFormatter(column_name):
     base_template = """
     <details style="overflow: visible;">
         <summary>{column_name}</summary>
@@ -59,6 +55,15 @@ def DictFormatter(column_name):
     return HTMLTemplateFormatter(template=base_template.replace('{column_name}', column_name))
 
 
+def DictFormatter(column_name):
+    base_template = """
+        <% _.each(value, function(vv, key) { %>
+            <li><b><%= key %>:</b> <%= vv %></li>
+        <% }); %>
+    """
+    return HTMLTemplateFormatter(template=base_template)
+
+
 class ExceptionFormatter:
     base_template = """
 <details style="overflow: visible;">
@@ -79,9 +84,9 @@ class ExceptionFormatter:
 
 tabulator_formatters = {
     'metrics': DictFormatter(column_name='metrics'),
-    'progress_': DictFormatter(column_name='progress'),
+    'progress_': FoldDictFormatter(column_name='progress'),
     'progress': progress_formatter,
-    'params': DictFormatter(column_name='params'),
+    'params': FoldDictFormatter(column_name='params'),
     'exception': HTMLTemplateFormatter(template=ExceptionFormatter.base_template),
 }
 
@@ -93,10 +98,56 @@ class ExceptionFormatter:
     'progress': None,
     'progress_': None,
     'exception': None,
-    'str': {'type': 'list', 'valuesLookup': True},
+    'note': {'type': 'list', 'valuesLookup': True},
+    'tags': {'type': 'list', 'valuesLookup': True},
 }
 
 
+def drop_nonscalar_metric(dic):
+    if not isinstance(dic, dict):
+        return
+
+    for k, v in list(dic.items()):
+        if not isinstance(v, numbers.Number):
+            dic.pop(k)
+    return dic
+
+
+def reformat_progress(dic):
+    if not isinstance(dic, dict):
+        return {
+            'ratio': '100%',
+            'color': 'yellow',
+        }
+
+    ratio = dic.get('ratio', 0)
+    end_code = dic.get('end_code', None)
+
+    # normal end ->  end_code == 0 -> green
+    # interrupt by exception ->  end_code > 0 -> red
+    # running -> end_code is None -> blue
+    # killed without any signal ( in 5 minute ) ->  end_code is None -> blue
+    # killed and dumped by watcher ->  end_code == -10 -> red
+
+    if end_code is None:
+        color = 'blue'
+    elif ratio == 1:
+        color = 'green'
+    elif end_code == 0:
+        color = 'green'
+    elif end_code > 0 or end_code < 0:
+        color = 'red'
+        if ratio == 0:
+            ratio = 0.01
+    else:
+        color = 'black'
+
+    return {
+        'ratio': f'{ratio:2%}',
+        'color': color,
+    }
+
+
 def make_experiment_tabular(df: pd.DataFrame):
     """
     {'start': '23-03-14-224651',
@@ -117,40 +168,11 @@ def make_experiment_tabular(df: pd.DataFrame):
         df['exception'] = {}
     else:
         df['exception'].fillna({})
+
     if 'tags' not in df.columns:
         df['tags'] = np.empty((len(df.index), 0)).tolist()
 
-    def reformat_progress(dic):
-        if not isinstance(dic, dict):
-            return {
-                'ratio': '100%',
-                'color': 'yellow',
-            }
-
-        ratio = dic.get('ratio', 0)
-        end_code = dic.get('end_code', None)
-
-        # normal end ->  end_code == 0 -> green
-        # interrupt by exception ->  end_code > 0 -> red
-        # running -> end_code is None -> blue
-        # killed without any signal ( in 5 minute ) ->  end_code is None -> blue
-        # killed and dumped by watcher ->  end_code == -10 -> red
-
-        if end_code is None:
-            color = 'blue'
-        elif ratio == 1:
-            color = 'green'
-        elif end_code == 0:
-            color = 'green'
-        elif end_code > 0 or end_code < 0:
-            color = 'red'
-            if ratio == 0:
-                ratio = 0.01
-
-        return {
-            'ratio': f'{ratio:2%}',
-            'color': color,
-        }
+    df['metrics'] = df['metrics'].apply(drop_nonscalar_metric)
 
     # df['progress_'] = df['progress']
     df['progress'] = df['progress'].apply(reformat_progress)
@@ -158,11 +180,14 @@ def reformat_progress(dic):
     # ratio = 1
     # ratio < 1, no-end-code ->
 
-    columns = set(df.columns) - {'git', 'paths', 'pinfo',
-                                 'execute', 'lock', 'params.yaml',
-                                 'params_hash', 'table_row', 'hooks', 'logger_args',
-                                 'agent', 'trainer', 'progress_',
-                                 'metric_board'}
+    extra_columns = set(df.columns) - {'git', 'paths', 'pinfo',
+                                       'execute', 'lock', 'params.yaml',
+                                       'params_hash', 'table_row', 'hooks', 'logger_args',
+                                       'agent', 'trainer', 'progress_',
+                                       'start', 'end',
+                                       'tensorboard_args',
+                                       'state',
+                                       'metric_board'}
     top_columns = [
         'exp_name', 'test_name',
         'progress',
@@ -171,9 +196,10 @@ def reformat_progress(dic):
         'note', 'tags',
     ]
 
-    columns = columns - set(top_columns)
+    extra_columns = extra_columns - set(top_columns)
+    [tabulator_editors.setdefault(k, None) for k in extra_columns]
 
-    df = df[top_columns + list(columns)]
+    df = df[top_columns + list(extra_columns)]
 
     def on_cell_change(e: TableEditEvent):
         nonlocal df

From 4eedf1694bb90ea6f2ee9acac2878905c85c4275 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 14:21:22 +0800
Subject: [PATCH 57/95] Watcher: avoid replacement when dump_info

---
 src/lumo/exp/watch.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index 727c6f3..97950f3 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -457,6 +457,7 @@ def progress(self, with_pandas=True):
                                       {
                                           'end': strftime(), 'end_code': -10,
                                           'msg': 'ended by watcher'}
+                                      , append=True
                                       )
                         os.remove(pid_f)
                 except:

From b798e19623af164d9fb7fa1b2423151d91c15536 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 14:21:40 +0800
Subject: [PATCH 58/95] trainer: fix small bugs

---
 src/lumo/trainer/base.py      | 2 +-
 src/lumo/trainer/callbacks.py | 6 ++++--
 src/lumo/trainer/trainer.py   | 8 +++++---
 3 files changed, 10 insertions(+), 6 deletions(-)

diff --git a/src/lumo/trainer/base.py b/src/lumo/trainer/base.py
index bab315f..26a5c06 100644
--- a/src/lumo/trainer/base.py
+++ b/src/lumo/trainer/base.py
@@ -134,7 +134,7 @@ def inner(dm=None, params=None, *args, **kwargs):
                 process_loader = getattr(self, 'process_loader', None)
                 if process_loader is not None:
                     process_loader(dm, TrainStage.create_from_str(func.__name__))
-                func(*args, **kwargs)
+                func(dm, params, *args, **kwargs)
 
             return inner
 
diff --git a/src/lumo/trainer/callbacks.py b/src/lumo/trainer/callbacks.py
index b842d40..dad473e 100644
--- a/src/lumo/trainer/callbacks.py
+++ b/src/lumo/trainer/callbacks.py
@@ -353,6 +353,7 @@ def __init__(self, step_frequence=3, break_in=1000):
         self.step = step_frequence
         file = tempfile.TemporaryFile('w')
         self.temp = file
+        self.cur_tqdm = None
 
     def on_imodels_end(self, trainer: Trainer, func, params: ParamsType, result: Any, *args, **kwargs):
         super().on_imodels_end(trainer, func, params, result, *args, **kwargs)
@@ -409,8 +410,9 @@ def update(self, trainer: Trainer):
     def flush(self, trainer: Trainer):
         """Flush"""
         self.c = 0
-        trainer.logger.inline(self.cur_tqdm)
-        trainer.logger.newline()
+        if self.cur_tqdm is not None:
+            trainer.logger.inline(self.cur_tqdm)
+            trainer.logger.newline()
 
     def on_train_epoch_begin(self, trainer: Trainer, func, params: ParamsType, *args, **kwargs):
         super().on_train_epoch_begin(trainer, func, params, *args, **kwargs)
diff --git a/src/lumo/trainer/trainer.py b/src/lumo/trainer/trainer.py
index 87bf43b..b714be0 100644
--- a/src/lumo/trainer/trainer.py
+++ b/src/lumo/trainer/trainer.py
@@ -610,6 +610,8 @@ def train(self, dm: Union[DataModule, DataLoaderType] = None, params: ParamsType
             ValueError: If no data loader is available for training.
 
         """
+        self.change_stage(TrainStage.train)
+
         loader = self.select_loader(dm)
         if not loader:
             loader = self.train_dataloader
@@ -816,8 +818,7 @@ def change_stage(self, stage: TrainStage):
             else:
                 v.eval()
 
-    @classmethod
-    def select_loader(cls, dm=None):
+    def select_loader(self, dm=None, stage=None):
         """
         Selects the appropriate loader based on the given data module.
 
@@ -830,7 +831,8 @@ def select_loader(cls, dm=None):
         loader = None
         if dm:
             if isinstance(dm, DataModule):
-                loader = dm.train_dataloader
+                loader = dm.get_loader_with_stage(stage=self.trainstage)
+                # loader = dm.train_dataloader
             elif isinstance(dm, DataLoader) or isinstance(dm, DataLoaderSide):
                 loader = dm
             else:

From d7c4fa9ce3d4962664fa8a4ef6297299dc48e547 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 14:21:50 +0800
Subject: [PATCH 59/95] run_command: typehint

---
 src/lumo/utils/subprocess.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lumo/utils/subprocess.py b/src/lumo/utils/subprocess.py
index c610905..749a793 100644
--- a/src/lumo/utils/subprocess.py
+++ b/src/lumo/utils/subprocess.py
@@ -13,7 +13,7 @@ def consume(p: subprocess.Popen):
             print(line, end='')
 
 
-def run_command(command, cwd=None, env=None, non_block=False):
+def run_command(command: str, cwd=None, env=None, non_block=False):
     """
     Executes a command in the shell and captures its standard output and standard error.
 

From 82655dad16ed27be965921c281b4b9877969ce01 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 14:21:59 +0800
Subject: [PATCH 60/95] contrib: importing

---
 src/lumo/contrib/__init__.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/lumo/contrib/__init__.py b/src/lumo/contrib/__init__.py
index a4f53fd..e4f1925 100644
--- a/src/lumo/contrib/__init__.py
+++ b/src/lumo/contrib/__init__.py
@@ -3,3 +3,4 @@
 """
 from .module.ema import EMA
 from .optim.grouper import ParamGrouper
+from .module.memoty_bank import MemoryBank, StorageBank

From ca8c10d762c2352c024c4acaa506bddee50944da Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 14:26:01 +0800
Subject: [PATCH 61/95] imagenet example

---
 examples/imagenet.py | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/examples/imagenet.py b/examples/imagenet.py
index 4a61e57..463ff14 100644
--- a/examples/imagenet.py
+++ b/examples/imagenet.py
@@ -192,7 +192,7 @@ def imodels(self, params: ParamsType):
     def train_step(self, batch, params: ParamsType = None) -> MetricType:
         super().train_step(batch, params)
         m = Meter()
-        eval_xs, xs, ys = batch['xs0'], batch['xs1'], batch['ys']
+        xs, ys = batch['xs'], batch['ys']
         logits = self.model(xs)
 
         Lall = F.cross_entropy(logits, ys)
@@ -205,8 +205,7 @@ def train_step(self, batch, params: ParamsType = None) -> MetricType:
 
         with torch.no_grad():
             m.mean.Lall = Lall
-            eval_logits = self.model(eval_xs)
-            m.mean.Ax = torch.eq(eval_logits.argmax(dim=-1), ys).float().mean()
+            m.mean.Ax = torch.eq(logits.argmax(dim=-1), ys).float().mean()
             m.last.lr = cur_lr
         return m
 

From a8b6f4b800f1186983a625ddc48f090592e9b556 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 14:27:31 +0800
Subject: [PATCH 62/95] example

---
 examples/imagenet.py | 4 ++--
 examples/moco.py     | 6 +++---
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/examples/imagenet.py b/examples/imagenet.py
index 463ff14..31208f3 100644
--- a/examples/imagenet.py
+++ b/examples/imagenet.py
@@ -234,8 +234,8 @@ def main():
     else:  # not distributed or in distribution environment
         # create datamodule to contain dataloader
         ds, test_ds = make_dataset(dummy=params.dummy)
-        dl = ds.DataLoader(batch_size=params.batch_size)
-        test_dl = test_ds.DataLoader(batch_size=params.batch_size)
+        dl = ds.DataLoader(batch_size=params.batch_size, num_workers=4)
+        test_dl = test_ds.DataLoader(batch_size=params.batch_size, num_workers=4)
         dm = DataModule()
         dm.regist_dataloader(train=dl, test=test_dl)
 
diff --git a/examples/moco.py b/examples/moco.py
index f911367..169aff9 100644
--- a/examples/moco.py
+++ b/examples/moco.py
@@ -267,9 +267,9 @@ def main():
     params.from_args()
 
     # create datamodule to contain dataloader
-    dl = ds.DataLoader(batch_size=params.batch_size)
-    memo_dl = memo_ds.DataLoader(batch_size=params.batch_size)
-    test_dl = test_ds.DataLoader(batch_size=params.batch_size)
+    dl = ds.DataLoader(batch_size=params.batch_size, num_workers=2)
+    memo_dl = memo_ds.DataLoader(batch_size=params.batch_size, num_workers=2)
+    test_dl = test_ds.DataLoader(batch_size=params.batch_size, num_workers=2)
     dm = DataModule()
     dm.regist_dataloader(train=dl,
                          test=test_dl,

From ddc59b570f8d815f7496955e344f13120bcec55f Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 15:08:28 +0800
Subject: [PATCH 63/95] test: Fix precision error

---
 tests/trainer/test_meter.py | 18 +++++++++++++-----
 1 file changed, 13 insertions(+), 5 deletions(-)

diff --git a/tests/trainer/test_meter.py b/tests/trainer/test_meter.py
index edf8fae..2956eb0 100644
--- a/tests/trainer/test_meter.py
+++ b/tests/trainer/test_meter.py
@@ -9,11 +9,10 @@ def test_ReduceItem():
         item.update(i)
     assert item.res == np.mean(range(200)[-ReduceItem.SLIDE_WINDOW_SIZE:], dtype=float).item()
 
-    item = ReduceItem([1, 2, 3], 'last')
+    item = ReduceItem(3, 'last')
     for i in range(4):
-        res = [j for j in range(i)]
-        item.update(res)
-        assert item.res == res
+        item.update(i)
+        assert item.res == i
 
     rand = [np.random.rand(4) for i in range(4)]
     avg = ReduceItem(rand[0], 'sum')
@@ -63,4 +62,13 @@ def test_avgmeter():
 
 
 def test_meter():
-    pass
+    from lumo import Meter, Record
+    import numpy as np
+    rnd = np.random.rand(1000)
+    r = Record()
+    m = Meter()
+    m.mean.rnd = rnd[:500]
+    r.record(m)
+    m.mean.rnd = rnd[500:]
+    r.record(m)
+    assert np.isclose(r.agg()['rnd'], rnd.mean())

From 81993b17683fa227c62c390640824fb67c7621d8 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 15:42:26 +0800
Subject: [PATCH 64/95] Make huggingface.accelerator an optional choice

---
 src/lumo/contrib/accelerate/__init__.py       |   1 -
 src/lumo/contrib/accelerate/data_loader.py    |  10 --
 src/lumo/contrib/accelerate/utils.py          |  30 -----
 src/lumo/contrib/module/memoty_bank.py        |  16 +--
 src/lumo/exp/exphook.py                       |   2 -
 src/lumo/trainer/accelerator.py               | 109 ++++++++++++++++++
 .../augments => trainer/backend}/__init__.py  |   0
 .../backend}/accelerator.py                   |   2 +-
 src/lumo/trainer/trainer.py                   |  40 ++-----
 src/lumo/{contrib => utils}/data/__init__.py  |   0
 src/lumo/utils/data/augments/__init__.py      |   0
 .../{contrib => utils}/data/augments/mix.py   |   0
 .../data/augments/transforms.py               |   0
 src/lumo/{contrib => utils}/data/splits.py    |   0
 src/lumo/utils/device.py                      |  96 +++++++++++++++
 tests/trainer/test_skip.py                    |   5 +-
 tests/trainer/test_trainer.py                 |   5 +-
 17 files changed, 227 insertions(+), 89 deletions(-)
 delete mode 100644 src/lumo/contrib/accelerate/__init__.py
 delete mode 100644 src/lumo/contrib/accelerate/data_loader.py
 delete mode 100644 src/lumo/contrib/accelerate/utils.py
 create mode 100644 src/lumo/trainer/accelerator.py
 rename src/lumo/{contrib/data/augments => trainer/backend}/__init__.py (100%)
 rename src/lumo/{contrib/accelerate => trainer/backend}/accelerator.py (93%)
 rename src/lumo/{contrib => utils}/data/__init__.py (100%)
 create mode 100644 src/lumo/utils/data/augments/__init__.py
 rename src/lumo/{contrib => utils}/data/augments/mix.py (100%)
 rename src/lumo/{contrib => utils}/data/augments/transforms.py (100%)
 rename src/lumo/{contrib => utils}/data/splits.py (100%)
 create mode 100644 src/lumo/utils/device.py

diff --git a/src/lumo/contrib/accelerate/__init__.py b/src/lumo/contrib/accelerate/__init__.py
deleted file mode 100644
index 59d25ad..0000000
--- a/src/lumo/contrib/accelerate/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-from .accelerator import Accelerator
\ No newline at end of file
diff --git a/src/lumo/contrib/accelerate/data_loader.py b/src/lumo/contrib/accelerate/data_loader.py
deleted file mode 100644
index f05ac57..0000000
--- a/src/lumo/contrib/accelerate/data_loader.py
+++ /dev/null
@@ -1,10 +0,0 @@
-from accelerate import synchronize_rng_states, DistributedType
-from accelerate.data_loader import DataLoaderDispatcher as _DataLoaderDispatcher, DataLoaderShard as _DataLoaderShard
-from accelerate.state import AcceleratorState
-from accelerate.utils import send_to_device
-
-from lumo import LumoDataLoader
-
-
-class DataLoaderDispatcher(_DataLoaderDispatcher):
-    pass
diff --git a/src/lumo/contrib/accelerate/utils.py b/src/lumo/contrib/accelerate/utils.py
deleted file mode 100644
index 44d29cc..0000000
--- a/src/lumo/contrib/accelerate/utils.py
+++ /dev/null
@@ -1,30 +0,0 @@
-from accelerate.utils import recursively_apply
-import torch
-
-
-def send_to_device(tensor, device, non_blocking=False):
-    """
-    Recursively sends the elements in a nested list/tuple/dictionary of tensors to a given device.
-
-    Args:
-        tensor (nested list/tuple/dictionary of `torch.Tensor`):
-            The data to send to a given device.
-        device (`torch.device`):
-            The device to send the data to.
-
-    Returns:
-        The same data structure as `tensor` with all tensors sent to the proper device.
-    """
-    if not isinstance(device, torch.device):
-        device = torch.device(device)
-
-    if 'mps' in device.type:
-        non_blocking = False
-
-    def _send_to_device(t, device):
-        return t.to(device, non_blocking=non_blocking)
-
-    def _has_to_method(t):
-        return hasattr(t, "to")
-
-    return recursively_apply(_send_to_device, tensor, device, test_type=_has_to_method)
diff --git a/src/lumo/contrib/module/memoty_bank.py b/src/lumo/contrib/module/memoty_bank.py
index d080c87..7c7477f 100644
--- a/src/lumo/contrib/module/memoty_bank.py
+++ b/src/lumo/contrib/module/memoty_bank.py
@@ -1,4 +1,4 @@
-from accelerate.utils import gather
+from torch import distributed
 from lumo.proc.dist import is_dist
 import torch.distributed
 from torch import nn
@@ -26,9 +26,9 @@ def __getitem__(self, item):
     @torch.no_grad()
     def scatter(self, name, value, index):
         value = value.detach()
-        value = gather(value)
+        value = distributed.gather(value)
         if isinstance(index, torch.Tensor):
-            index = gather(index)
+            index = distributed.gather(index)
         self[name][index] = value
 
 
@@ -61,7 +61,7 @@ def push(self, name, value):
             raise AssertionError()
 
         value = value.detach()
-        value = gather(value)
+        value = distributed.gather(value)
         ptr = self.offsets[name]
         k = self.sizes[name]
         batch_size = value.shape[0]
@@ -80,9 +80,9 @@ def batch_shuffle_ddp(x):
     """
     if not is_dist():
         return x, torch.arange(len(x))
-    # gather from all gpus
+    # distributed.gather from all gpus
     batch_size_this = x.shape[0]
-    x_gather = gather(x)
+    x_gather = distributed.gather(x)
     batch_size_all = x_gather.shape[0]
 
     num_gpus = batch_size_all // batch_size_this
@@ -111,9 +111,9 @@ def batch_unshuffle_ddp(x, idx_unshuffle):
     """
     if not is_dist():
         return x
-    # gather from all gpus
+    # distributed.gather from all gpus
     batch_size_this = x.shape[0]
-    x_gather = gather(x)
+    x_gather = distributed.gather(x)
     batch_size_all = x_gather.shape[0]
 
     num_gpus = batch_size_all // batch_size_this
diff --git a/src/lumo/exp/exphook.py b/src/lumo/exp/exphook.py
index 90f2c0b..f0c25d0 100644
--- a/src/lumo/exp/exphook.py
+++ b/src/lumo/exp/exphook.py
@@ -198,11 +198,9 @@ def on_start(self, exp: Experiment, *args, **kwargs):
                          'joblib',
                          'fire',
                          'psutil',
-                         'accelerate',
                          'hydra',
                          'omegaconf',
                          'decorator',
-
                          'numpy',
                          'torch',
                          )
diff --git a/src/lumo/trainer/accelerator.py b/src/lumo/trainer/accelerator.py
new file mode 100644
index 0000000..ab28ca3
--- /dev/null
+++ b/src/lumo/trainer/accelerator.py
@@ -0,0 +1,109 @@
+import warnings
+from torch import nn
+import torch
+from torch import distributed
+from torch.utils.data import DataLoader
+from lumo.data.loader import DataLoaderSide
+
+
+class Accelerator:
+    def __init__(self, **kwargs):
+        self._prop = kwargs
+
+    @property
+    def device(self):
+        return self._prop.get('device', None)
+
+    def set_device(self, device):
+        assert isinstance(device, torch.device)
+        self._prop['device'] = device
+
+    def prepare_data_loader(self, dataloader):
+        return dataloader
+
+    def prepare_model(self, model: torch.nn.Module):
+        return model.to(self.device)
+
+    def prepare_optimizer(self, optimizer: torch.optim.Optimizer):
+        return optimizer
+
+    def unwrap_model(self, model):
+        return model
+
+    def prepare(self, *args):
+        res = []
+        for item in args:
+            if isinstance(item, nn.Module):
+                res.append(self.prepare_model(item))
+            elif isinstance(item, (DataLoader, DataLoaderSide)):
+                res.append(self.prepare_data_loader(item))
+            elif isinstance(item, torch.optim.Optimizer):
+                res.append(self.prepare_optimizer(item))
+            else:
+                raise NotImplementedError()
+        return res
+
+    def wait_for_everyone(self):
+        torch.distributed.barrier()
+
+    def gather(self, tensor: torch.Tensor):
+        if tensor.ndim == 0:
+            tensor = tensor.clone()[None]
+        output_tensors = [tensor.clone() for _ in range(torch.distributed.get_world_size())]
+        distributed.all_gather(output_tensors, tensor)
+        return torch.cat(output_tensors, dim=0)
+
+
+class HugAccelerator(Accelerator):
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        from .backend.accelerator import Accelerator
+        self._backbone = Accelerator()
+
+    @property
+    def device(self):
+        return self._backbone.device
+
+    def set_device(self, device: torch.device):
+        assert isinstance(device, torch.device)
+        self._backbone.state.device = device
+
+    def prepare_data_loader(self, loader):
+        from accelerate.data_loader import DataLoaderShard, DataLoaderDispatcher
+        if isinstance(loader, (DataLoaderShard, DataLoaderDispatcher)):
+            warnings.warn('Duplicated prepare a same DataLoader twice, check your code.')
+            return loader
+        return self._backbone.prepare_data_loader(loader)
+
+    def prepare_model(self, model):
+        return self._backbone.prepare_model(model)
+
+    def prepare_optimizer(self, optimizer):
+        return self._backbone.prepare_optimizer(optimizer)
+
+    def unwrap_model(self, model):
+        return self._backbone.unwrap_model(model)
+
+    def prepare(self, *args):
+        return self._backbone.prepare(*args)
+
+    def wait_for_everyone(self):
+        self._backbone.wait_for_everyone()
+
+    def gather(self, tensor):
+        return self._backbone.gather(tensor)
+
+
+register = {
+
+    'none': Accelerator,
+    'accelerator': HugAccelerator,
+    'deepspeed': None,
+    'horovod': None,
+}
+
+
+def get_accelerator(name: str, **kwargs):
+    assert name not in register, ', '.join(register.keys())
+    return register[name](**kwargs)
diff --git a/src/lumo/contrib/data/augments/__init__.py b/src/lumo/trainer/backend/__init__.py
similarity index 100%
rename from src/lumo/contrib/data/augments/__init__.py
rename to src/lumo/trainer/backend/__init__.py
diff --git a/src/lumo/contrib/accelerate/accelerator.py b/src/lumo/trainer/backend/accelerator.py
similarity index 93%
rename from src/lumo/contrib/accelerate/accelerator.py
rename to src/lumo/trainer/backend/accelerator.py
index 79d4d3b..488e539 100644
--- a/src/lumo/contrib/accelerate/accelerator.py
+++ b/src/lumo/trainer/backend/accelerator.py
@@ -10,7 +10,7 @@ class Accelerator(_Accelerator):
     the device of data will be controlled by Trainer rather than Accelerator.
     """
 
-    def prepare_data_loader(self, data_loader):
+    def prepare_data_loader(self, data_loader, **kwargs):
         return prepare_data_loader(
             data_loader,
             None,  # None instead of self.device,
diff --git a/src/lumo/trainer/trainer.py b/src/lumo/trainer/trainer.py
index b714be0..6489f8a 100644
--- a/src/lumo/trainer/trainer.py
+++ b/src/lumo/trainer/trainer.py
@@ -1,22 +1,16 @@
 import bisect
 import os
-import sys
 import warnings
-from datetime import datetime
 from functools import lru_cache
-from pprint import pformat
 from typing import Union, Dict, Any, Optional, Sequence, Mapping, Callable
 
 import numpy as np
 import torch
-from accelerate import DistributedDataParallelKwargs
-from accelerate.data_loader import DataLoaderDispatcher, DataLoaderShard
+from .accelerator import get_accelerator
 from torch import nn
 from torch.optim import Optimizer
 from torch.utils.data import DataLoader
-import json
-from lumo.contrib.accelerate import Accelerator
-from lumo.contrib.accelerate.utils import send_to_device
+from lumo.utils.device import send_to_device
 from lumo.core import TrainStage, Record, MetricType, Meter
 from lumo.core.disk import TableRow, Metrics
 from lumo.data import DataModule
@@ -30,11 +24,6 @@
 from .components import TrainerExperiment, TrainerParams
 from .saver import Saver
 
-# overwrite send_to_device to resolve https://github.com/pytorch/pytorch/issues/83015
-# from accelerate import Accelerator
-# from accelerate.utils import send_to_device
-from ..utils.fmt import strftime, indent_print
-
 ParamsType = TrainerParams
 
 
@@ -74,7 +63,7 @@ def __init_subclass__(cls, **kwargs):
             raise TypeError(
                 f"Can't instantiate abstract class {cls.__name__} directly, please create a subclass of it.")
 
-    def __init__(self, params: ParamsType, dm: DataModule = None):
+    def __init__(self, params: ParamsType, dm: DataModule = None, accelerator='accelerator'):
         if dm is None:
             dm = DataModule(params)
         else:
@@ -100,13 +89,12 @@ def __init__(self, params: ParamsType, dm: DataModule = None):
         self.train_toggle = False
 
         device = params.get('device', None) if not self.is_dist else None
+        # self.accelerate = Accelerator(kwargs_handlers=[
+        #     DistributedDataParallelKwargs(find_unused_parameters=params.get('find_unused_parameters', False))
+        # ])
+        self.accelerate = get_accelerator(accelerator)
 
-        self.accelerate = Accelerator(kwargs_handlers=[
-            DistributedDataParallelKwargs(find_unused_parameters=params.get('find_unused_parameters', False))
-        ])
-
-        if self.accelerate.state.distributed_type == self.accelerate.state.distributed_type.NO:
-            self.accelerate.state.device = torch.device(device)
+        self.accelerate.set_device(torch.device(device))
 
         if dist.is_main():
             self.params.to_yaml(self.exp.params_fn)
@@ -405,7 +393,7 @@ def device(self):
         Returns:
             The device used for training.
         """
-        return self.accelerate.device
+        return torch.device(self.params.device)
 
     def _load_fun_state_dict(self, src: dict):
         """
@@ -577,17 +565,7 @@ def prepare_dataloader(self, loader: DataLoaderType, stage: TrainStage = None):
         :param stage:
         :return:
         """
-        if isinstance(loader, (DataLoaderShard, DataLoaderDispatcher)):
-            warnings.warn('Duplicated prepare a same DataLoader twice, check your code.')
-            return loader
-
-        split_batches = self.params.get('split_batches', None)
-        if stage is not None and not stage.is_train():
-            split_batches = True
-
-        """do not change original loader stage"""
         if isinstance(loader, DataLoader):
-            self.accelerate.split_batches = split_batches
             loader = self.accelerate.prepare_data_loader(loader)
         elif isinstance(loader, DataLoaderSide):
             loader = loader.copy()
diff --git a/src/lumo/contrib/data/__init__.py b/src/lumo/utils/data/__init__.py
similarity index 100%
rename from src/lumo/contrib/data/__init__.py
rename to src/lumo/utils/data/__init__.py
diff --git a/src/lumo/utils/data/augments/__init__.py b/src/lumo/utils/data/augments/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/lumo/contrib/data/augments/mix.py b/src/lumo/utils/data/augments/mix.py
similarity index 100%
rename from src/lumo/contrib/data/augments/mix.py
rename to src/lumo/utils/data/augments/mix.py
diff --git a/src/lumo/contrib/data/augments/transforms.py b/src/lumo/utils/data/augments/transforms.py
similarity index 100%
rename from src/lumo/contrib/data/augments/transforms.py
rename to src/lumo/utils/data/augments/transforms.py
diff --git a/src/lumo/contrib/data/splits.py b/src/lumo/utils/data/splits.py
similarity index 100%
rename from src/lumo/contrib/data/splits.py
rename to src/lumo/utils/data/splits.py
diff --git a/src/lumo/utils/device.py b/src/lumo/utils/device.py
new file mode 100644
index 0000000..2e49881
--- /dev/null
+++ b/src/lumo/utils/device.py
@@ -0,0 +1,96 @@
+from typing import Any, Mapping
+import torch
+
+
+def honor_type(obj, generator):
+    """
+    Cast a generator to the same type as obj (list, tuple, or namedtuple)
+    """
+    try:
+        return type(obj)(generator)
+    except TypeError:
+        # Some objects may not be able to instantiate from a generator directly
+        return type(obj)(*list(generator))
+
+
+def is_torch_tensor(tensor):
+    return isinstance(tensor, torch.Tensor)
+
+
+def recursively_apply(func, data, *args, test_type=is_torch_tensor, error_on_other_type=False, **kwargs):
+    """
+    Recursively apply a function on a data structure that is a nested list/tuple/dictionary of a given base type.
+
+    Args:
+        func (`callable`):
+            The function to recursively apply.
+        data (nested list/tuple/dictionary of `main_type`):
+            The data on which to apply `func`
+        *args:
+            Positional arguments that will be passed to `func` when applied on the unpacked data.
+        main_type (`type`, *optional*, defaults to `torch.Tensor`):
+            The base type of the objects to which apply `func`.
+        error_on_other_type (`bool`, *optional*, defaults to `False`):
+            Whether to return an error or not if after unpacking `data`, we get on an object that is not of type
+            `main_type`. If `False`, the function will leave objects of types different than `main_type` unchanged.
+        **kwargs:
+            Keyword arguments that will be passed to `func` when applied on the unpacked data.
+
+    Returns:
+        The same data structure as `data` with `func` applied to every object of type `main_type`.
+    """
+    if isinstance(data, (tuple, list)):
+        return honor_type(
+            data,
+            (
+                recursively_apply(
+                    func, o, *args, test_type=test_type, error_on_other_type=error_on_other_type, **kwargs
+                )
+                for o in data
+            ),
+        )
+    elif isinstance(data, Mapping):
+        return type(data)(
+            {
+                k: recursively_apply(
+                    func, v, *args, test_type=test_type, error_on_other_type=error_on_other_type, **kwargs
+                )
+                for k, v in data.items()
+            }
+        )
+    elif test_type(data):
+        return func(data, *args, **kwargs)
+    elif error_on_other_type:
+        raise TypeError(
+            f"Can't apply {func.__name__} on object of type {type(data)}, only of nested list/tuple/dicts of objects "
+            f"that satisfy {test_type.__name__}."
+        )
+    return data
+
+
+def send_to_device(tensor, device, non_blocking=False):
+    """
+    Recursively sends the elements in a nested list/tuple/dictionary of tensors to a given device.
+
+    Args:
+        tensor (nested list/tuple/dictionary of `torch.Tensor`):
+            The data to send to a given device.
+        device (`torch.device`):
+            The device to send the data to.
+
+    Returns:
+        The same data structure as `tensor` with all tensors sent to the proper device.
+    """
+    if not isinstance(device, torch.device):
+        device = torch.device(device)
+
+    if 'mps' in device.type:
+        non_blocking = False
+
+    def _send_to_device(t, device):
+        return t.to(device, non_blocking=non_blocking)
+
+    def _has_to_method(t):
+        return hasattr(t, "to")
+
+    return recursively_apply(_send_to_device, tensor, device, test_type=_has_to_method)
diff --git a/tests/trainer/test_skip.py b/tests/trainer/test_skip.py
index 966af2a..2fa2c27 100644
--- a/tests/trainer/test_skip.py
+++ b/tests/trainer/test_skip.py
@@ -57,9 +57,8 @@ def to_device(self, item: Optional[Union[nn.Module, torch.Tensor, Sequence, Mapp
                   device_args_kwargs=None):
         return super().to_device(item, device_args_kwargs)
 
-    def prepare_dataloader(self, stage: TrainStage, dataloader=None):
-        # assert self.context == 'prepare_dataloader'
-        return super().prepare_dataloader(stage, dataloader)
+    def prepare_dataloader(self, loader: DataLoaderType, stage: TrainStage = None):
+        return super().prepare_dataloader(loader, stage)
 
     def initialize(self):
         if not self.is_initialized:
diff --git a/tests/trainer/test_trainer.py b/tests/trainer/test_trainer.py
index 38c015c..a75fa94 100644
--- a/tests/trainer/test_trainer.py
+++ b/tests/trainer/test_trainer.py
@@ -72,9 +72,8 @@ def to_device(self, item: Optional[Union[nn.Module, torch.Tensor, Sequence, Mapp
                   device_args_kwargs=None):
         return super().to_device(item, device_args_kwargs)
 
-    def prepare_dataloader(self, stage: TrainStage, dataloader=None):
-        # assert self.context == 'prepare_dataloader'
-        return super().prepare_dataloader(stage, dataloader)
+    def prepare_dataloader(self, loader: DataLoaderType, stage: TrainStage = None):
+        return super().prepare_dataloader(loader, stage)
 
     def initialize(self):
         if not self.is_initialized:

From 492aaf4bde7d6e939f5cbc1687dd8c66d5d48490 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 15:45:55 +0800
Subject: [PATCH 65/95] Make huggingface.accelerator an optional choice

---
 src/lumo/trainer/accelerator.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lumo/trainer/accelerator.py b/src/lumo/trainer/accelerator.py
index ab28ca3..12eb0ea 100644
--- a/src/lumo/trainer/accelerator.py
+++ b/src/lumo/trainer/accelerator.py
@@ -105,5 +105,5 @@ def gather(self, tensor):
 
 
 def get_accelerator(name: str, **kwargs):
-    assert name not in register, ', '.join(register.keys())
+    assert name in register, ', '.join(register.keys())
     return register[name](**kwargs)

From b5be9cc41541b06208b0bd966c76e016f3de15a8 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 15:48:52 +0800
Subject: [PATCH 66/95] Make huggingface.accelerator an optional choice

---
 src/lumo/trainer/accelerator.py | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/src/lumo/trainer/accelerator.py b/src/lumo/trainer/accelerator.py
index 12eb0ea..2458933 100644
--- a/src/lumo/trainer/accelerator.py
+++ b/src/lumo/trainer/accelerator.py
@@ -53,6 +53,9 @@ def gather(self, tensor: torch.Tensor):
         distributed.all_gather(output_tensors, tensor)
         return torch.cat(output_tensors, dim=0)
 
+    def backward(self, loss: torch.Tensor, **kwargs):
+        loss.backward(**kwargs)
+
 
 class HugAccelerator(Accelerator):
 
@@ -94,6 +97,9 @@ def wait_for_everyone(self):
     def gather(self, tensor):
         return self._backbone.gather(tensor)
 
+    def backward(self, loss: torch.Tensor, **kwargs):
+        self._backbone.backward(loss, **kwargs)
+
 
 register = {
 
@@ -104,6 +110,6 @@ def gather(self, tensor):
 }
 
 
-def get_accelerator(name: str, **kwargs):
+def get_accelerator(name: str, **kwargs) -> Accelerator:
     assert name in register, ', '.join(register.keys())
     return register[name](**kwargs)

From c25cd01b80378cae148b98ffbe08fe99bb71b9ef Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 16:36:07 +0800
Subject: [PATCH 67/95] Gather method

---
 src/lumo/contrib/module/memoty_bank.py | 17 +++++++++--------
 src/lumo/proc/dist.py                  | 10 ++++++++++
 src/lumo/trainer/accelerator.py        |  7 ++-----
 3 files changed, 21 insertions(+), 13 deletions(-)

diff --git a/src/lumo/contrib/module/memoty_bank.py b/src/lumo/contrib/module/memoty_bank.py
index 7c7477f..a73dfe5 100644
--- a/src/lumo/contrib/module/memoty_bank.py
+++ b/src/lumo/contrib/module/memoty_bank.py
@@ -1,6 +1,7 @@
 from torch import distributed
-from lumo.proc.dist import is_dist
+from lumo.proc.dist import is_dist, gather
 import torch.distributed
+
 from torch import nn
 import torch
 
@@ -26,9 +27,9 @@ def __getitem__(self, item):
     @torch.no_grad()
     def scatter(self, name, value, index):
         value = value.detach()
-        value = distributed.gather(value)
+        value = gather(value)
         if isinstance(index, torch.Tensor):
-            index = distributed.gather(index)
+            index = gather(index)
         self[name][index] = value
 
 
@@ -61,7 +62,7 @@ def push(self, name, value):
             raise AssertionError()
 
         value = value.detach()
-        value = distributed.gather(value)
+        value = gather(value)
         ptr = self.offsets[name]
         k = self.sizes[name]
         batch_size = value.shape[0]
@@ -80,9 +81,9 @@ def batch_shuffle_ddp(x):
     """
     if not is_dist():
         return x, torch.arange(len(x))
-    # distributed.gather from all gpus
+    # gather from all gpus
     batch_size_this = x.shape[0]
-    x_gather = distributed.gather(x)
+    x_gather = gather(x)
     batch_size_all = x_gather.shape[0]
 
     num_gpus = batch_size_all // batch_size_this
@@ -111,9 +112,9 @@ def batch_unshuffle_ddp(x, idx_unshuffle):
     """
     if not is_dist():
         return x
-    # distributed.gather from all gpus
+    # gather from all gpus
     batch_size_this = x.shape[0]
-    x_gather = distributed.gather(x)
+    x_gather = gather(x)
     batch_size_all = x_gather.shape[0]
 
     num_gpus = batch_size_all // batch_size_this
diff --git a/src/lumo/proc/dist.py b/src/lumo/proc/dist.py
index f960bff..ad48d14 100644
--- a/src/lumo/proc/dist.py
+++ b/src/lumo/proc/dist.py
@@ -75,3 +75,13 @@ def is_main():
 
     """
     return local_rank() <= 0
+
+
+def gather(tensor):
+    if dist.is_initialized():
+        if tensor.ndim == 0:
+            tensor = tensor.clone()[None]
+        output_tensors = [tensor.clone() for _ in range(torch.distributed.get_world_size())]
+        torch.distributed.all_gather(output_tensors, tensor)
+        return torch.cat(output_tensors, dim=0)
+    return tensor
diff --git a/src/lumo/trainer/accelerator.py b/src/lumo/trainer/accelerator.py
index 2458933..c7e873f 100644
--- a/src/lumo/trainer/accelerator.py
+++ b/src/lumo/trainer/accelerator.py
@@ -4,6 +4,7 @@
 from torch import distributed
 from torch.utils.data import DataLoader
 from lumo.data.loader import DataLoaderSide
+from lumo.proc.dist import gather
 
 
 class Accelerator:
@@ -47,11 +48,7 @@ def wait_for_everyone(self):
         torch.distributed.barrier()
 
     def gather(self, tensor: torch.Tensor):
-        if tensor.ndim == 0:
-            tensor = tensor.clone()[None]
-        output_tensors = [tensor.clone() for _ in range(torch.distributed.get_world_size())]
-        distributed.all_gather(output_tensors, tensor)
-        return torch.cat(output_tensors, dim=0)
+        return gather(tensor)
 
     def backward(self, loss: torch.Tensor, **kwargs):
         loss.backward(**kwargs)

From 1fe265cbe0e39f54ae223ad60a0070688e9e20ed Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 16:45:47 +0800
Subject: [PATCH 68/95] Document

---
 README.ch.md | 229 ++++++++++++++++++++++-----------------------------
 1 file changed, 98 insertions(+), 131 deletions(-)

diff --git a/README.ch.md b/README.ch.md
index afbb779..209904b 100644
--- a/README.ch.md
+++ b/README.ch.md
@@ -2,184 +2,151 @@
 
 [![PyPI version](https://badge.fury.io/py/lumo.svg)](https://badge.fury.io/py/lumo)
 ![Python-Test](https://github.com/pytorch-lumo/lumo/actions/workflows/python-test.yml/badge.svg)
-[![license](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/pytorch-lumo/lumo/blob/master/LICENSE)
+[![license](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/Lightning-AI/lightning/blob/master/LICENSE)
+![Python-doc](./images/docstr_coverage_badge.svg)
 
+`lumo` 是一个精简高效的库，简化了实验所需的所有组件的管理，并特别关注增强深度学习实践者的体验。
 
-`lumo`：轻量、可扩展、功能解耦合的 Pytorch 实验框架。
+- 实验管理：: 为每次运行分配唯一路径，区分不同类型的文件并存储；并通过 git 管理代码快照。
+- 参数管理：基于 fire 提供比 argparser 更便捷的参数管理
+- 运行时配置：提供多级作用域下的配置管理
+- 可视化：基于 [Panel](https://panel.holoviz.org/index.html) 提供可交互的 jupyter 实验管理面板
+- 为深度学习提供额外的优化
+    - 训练：基于 Trainer 提供可任意扩展的训练逻辑简化，并提供完善的回调逻辑
+    - 优化器：参数与优化器构建一体化
+    - 数据: 数据集构建流程抽象、组合多个 DataLoader、...
+    - 分布式训练：同样支持多种训练加速框架，统一抽象，方便随时切换
+- 更多工具类...
 
-lumo 的设计理念：
+# :book: 目录
 
-- 模块解耦合：所有模块可以单独作为您现在使用的框架中的一个插件使用（而不像其他框架几乎耦合在一起）
-- 恰到好处的抽象：和模型相关的细节完全由使用者掌控，lumo 只封装了外部通用逻辑（而不像其他一些框架会代理模型初始化或损失迭代）
-- 覆盖整个生命周期：数据集构建、模型初始化、随机种子、训练/测试...，lumo 为所有步骤提供了功能包或流程简化
-- 极强的可扩展性：从单文件到包含多个领域多个方法的项目，lumo 都可以提供舒适的使用体验。已在两个领域有复现项目的最佳实践示例（见[Related Work](#Related Work)）。
+- [安装](#安装)
+- [快速开始](#快速开始)
 
-# 如何使用
+# :cloud: 安装
 
-## 安装
-
-从 pypi 或 github 主页安装最新的稳定版本：
+安装已发布的通过了所有测试的版本
 
 ```bash
 pip install -U lumo
-pip install git+https://github.com/pytorch-lumo/lumo
 ```
 
+或从 dev1 分支安装最新版本：
 
-## 快速开始
-
-本节包含 lumo 最常用的几个子功能，帮助使用者快速利用这些功能减少已有项目中的冗余代码，这些功能包括：
-
-- 一些常用功能的更优替代，如 [Params](#参数控制)（arguments 的平替），[Logger](#变量&日志记录)（logging 的平替）
-- 一些训练过程中部份流程的优化，如 [Experiment](#路径管理&版本控制)（提供无重复的实验路径管理、基于 git 的版本控制），[DatasetBuilder](#数据集构建)（更快构建数据集），
-
-### 参数控制
-
-`argparse` 的更优替代。`Params` 底层依托于 [omegaconf](https://github.com/omry/omegaconf) 和 [fire](https://github.com/google/python-fire)
-，只需要简单的配置，就可以从文件、命令行中读取参数。
-
-直接基于 Params 类定义参数：
-
-```python
-# python main.py --epoch=30 --dataset=100
-from lumo import Params
+```bash
+pip install git+https://github.com/pytorch-lumo/lumo
+```
 
-params = Params()
-params.epoch = 20
-# 集成优化器参数，自带补全提示
-params.optim = params.OPTIM.create_optim('Adam', lr=0.0001, weight_decay=4e-5)
-# 数据集只能从 cifar10/cifar100 中选择，且默认为 cifar10，其他的选择会报错
-params.dataset = params.choice('cifar10', 'cifar100')
+实验面板依赖于 panel，需要额外安装：
 
-# 从命令行参数中更新
-params.from_args()
-print(params.epoch)  # -> 30
-print(params.dataset)  # -> cifar100
-
-# 保存到文件
-params.to_json('./config.json')
-params.to_yaml('./config.yaml')
-# 从文件中更新
-params.from_json('./config.json')
-params.from_yaml('./config.yaml')
+```
+pip install panel
 ```
 
-也可以通过继承、多重继承来嵌套，组合参数。即使在命令行中输入了不存在的参数，Params 也会正常读取。 
+# :book: 快速开始
 
-### 变量&日志记录
+以下是两个经典场景：
 
-`logging` 的更优替代。通过 Meter、Record 和 Logger，可以实现变量的记录和格式化输出。其中：
+## :small_orange_diamond: 已有项目嵌入
 
-- Meter 记录单次的值
-- Record 以一定规则归约 Meter 实例（如 mean、sum 等）
-- Logger 用于代替 logging，除常用的 info、warn 等方法外，还提供了 inline 方法，可以在屏幕能单行更新（实际中，屏幕打印时间远小于训练时间，因此单行更新带来的时间开销可以忽略不计）。
+对已有项目，可以通过以下方式快速嵌入
 
 ```python
 import random
-import time
+from lumo import SimpleExperiment, Params, Logger, Meter, Record
 
-from lumo import Record, Meter, Logger
+logger = Logger()
+# 定义及使用，无需转换
+exp = SimpleExperiment(exp_name='my_exp_a')  # 为每种实验手动定义唯一名称
+exp.start()
+logger.add_log_dir(exp.mk_ipath())
 
-log = Logger()
+# 替换基于 argparse 等的参数定义方法
+params = Params()
+params.dataset = params.choice('cifar10', 'cifar100')
+params.alpha = params.arange(default=1, left=0, right=10)
+params.from_args()  # python3 train.py --dataset=cifar100 --alpha=0.2
+print(params.to_dict())  # {"dataset": "cifar100", "alpha": 0.2}
 
-record = Record()
-for idx in range(256):
-    meter = Meter()
-    meter.last.i = idx
-    meter.sum.acc = idx
-    meter.mean.loss = random.random()
-
-    record.record(meter)
-    log.inline(record)  # 单行更新
-    time.sleep(0.5)
-    if idx % 50 == 0:
-        log.newline()
-        record.clear()
-
-log.info(record)
-```
+# 记录实验参数
+exp.dump_info('params', params.to_dict())
+print(exp.test_name)  # 为每次实验自动分配唯一名称
 
-### 路径管理&版本控制
+# 基于命名空间提供本次实验的唯一路径
+# 元数据和二进制大文件分离，方便清理
+params.to_yaml(exp.mk_ipath('params.yaml'))
 
-`Experiment` 主要提供路径管理，可以为每一次试验根据实验名、日期、次数等自动提供不一样的保存路径。此外，Experiment 还可以通过 hook
-提供如代码版本管理、元数据记录等功能。在实验中，可以使用其子类 `SimpleExperiment` 实现大部分需求。
+for i in range(10):
+    # 记录实验指标
+    max_acc = exp.dump_metric('Acc', random.random(), cmp='max')
+    logger.info(f'Max acc {max_acc}')
 
-```python
-from lumo import SimpleExperiment
-from lumo import Params
+    # 存储大文件/二进制文件（如模型权重）
+    ckpt_fn = exp.mk_bpath('checkpoints', f'model_{i}.ckpt')
+    ...  # 保存代码 given ckpt_fn
 
-pm = Params()
-pm.module = 'example'
-pm.from_args()
+record = Record()
+for batch in range(10):
+    m = Meter()
+    m.mean.Lall = random.random()
+    m.last.lr = batch
+    record.record(m)
+    logger.info(record)
+
+# 主动结束实验，补充元信息。也可以在进程结束后由 hook 自动结束，支持针对异常的记录
+exp.end()
+```
 
-# 注册该次实验，实验名为 `pm.module`
-exp = SimpleExperiment(pm.module)
-# 实验开始，该方法会调用已注册的 ExpHooks，完成代码版本控制等功能。
-exp.start()
+## :small_orange_diamond: 从零开始
 
-# 小数据通过 `.test_file()` 获得路径
-fn = exp.test_file('params.json')
-pm.to_json(fn)
+如果从新开始一个深度学习实验，那么可以使用 lumo 全方位的加速代码的构建，下面提供了多个不同规模下使用 lumo 训练的示例：
 
-# 大文件通过 `.blob_file()` 获得路径（这是约定，而不是强制，大文件也可以保存到 `.test_file()` 中）
-fn = exp.blob_file('checkpoint.pt')
-with open(fn, 'w') as w:
-    w.write('write big data in blob file')
+单文件：
 
-print(exp.test_root)
-print(exp.get_prop('git'))  # see git commit history
-exp.end()
-```
+| 示例                                     | CoLab | 代码行数 |
+|----------------------------------------|-------|------|
+| [MNIST 示例](./examples/mnist.py)        |       | 118  |
+| [MocoV2 训练 CIFAR10](./examples/moco.py) || 284   |
+| [多卡训练 ImageNet]()                      |||
 
-### 数据集构建
+实验项目：
 
-![DatasetBuilder](./images/DatasetBuilder.png)
+| 项目                     | 说明                       |
+|------------------------|--------------------------|
+| [image-classification] | 集成了全监督、半监督、自监督的多个论文的复现代码 |
+| [emotion-recognition]  | 集成了情感分类、多模态情感分类的多个论文的复现代码 |
 
-`DatasetBuilder` 是采用有向无环图思路设计的数据集构建类，该类提供了一个恰当的抽象逻辑，避免了在一个实验里定义多个重复 Datasets 类。
+## :small_orange_diamond: 可视化界面
 
-`DatasetBuilder `将数据集的构件划分为输入-输出两阶段，同时提供 `.chain()`（序列格式）和`.zip()`（字典格式） 两种输出方式。
+在 jupyter 中：
 
 ```python
-from lumo import DatasetBuilder
-from torchvision.transforms import transforms
-import torch
-
-# Create a mnist-like dummy dataset
-db = (
-    DatasetBuilder()
-        .add_input("xs", torch.rand(500, 28, 28))
-        .add_input("ys", torch.randint(0, 10, (500,)))
-        .add_idx('id')
-        .add_output("xs", "xs1", transforms.RandomHorizontalFlip())
-        .add_output("xs", "xs2", )
-        .add_output("ys", "ys")
-)
-# Watch dataset structure
-print(db)
-# Builder(flow={'::idx::': ['id'], 'xs': ['xs1', 'xs2'], 'ys': ['ys']}, sized=True, size=500, iterable=True)
-
-print(db[0])
-# dict_keys(['id', 'xs1', 'xs2', 'ys'])
-```
+from lumo import Watcher
 
-# 更多教程
+w = Watcher()
+df = w.load()
+widget = w.panel(df)
+widget.servable()
+```
 
-# Related Work
+![Panel](./images/panel-example.png)
 
-- [image-classification](https://github.com/pytorch-lumo/image-classification): supervised/semi-supervised/self-supervised/noisy label learning on image-classfication
-  field. (suporrted datasets: CIFAR10/CIFAR100/STL-10/SVHN/ImageNet/tinyimagenet)
-- [emotion-recognition-in-conversation](https://github.com/pytorch-lumo/emotion-recognition-in-conversation):Multimodel emotional recognition on conversation. (suporrted datasets: IEMOCAP/MELD/MOSEI) 
+将按手动条件过滤后的实验筛选出来：
+![Panel](./images/panel-example2.png)
 
+可以直接使用命令行打开页面查看当前所有实验：
 
-# Acknowledge
+```
+lumo board [--port, --address, --open]
+```
 
- 一个人维护一个库四年，背后的动力是我持续不断的使用，感谢 lumo 陪我见证我的学术生涯。lumo 确实不一定适合所有人的习惯，但一定最适合我自己。lumo 取自 lumos，这是哈利波特里魔法杖发光的咒语。torch 是火炬，ignite 是点燃，所以 lumo 也向往着发光发热，希望 lumo 给大家带来美好的使用体验。
+# More
 
-# License 
+# :pencil: Acknowledge
 
-Distributed under the GNU General Public License 3.0. See [LICENSE](./LICENSE) for more information.
+从 2020 年维护至今。感谢 lumo 陪我见证我的学术生涯。
 
-# Contact
+# :scroll: License
 
- - [sailist@outlook.com](mailto:sailist@outlook.com)
+采用 [GNU General Public License 3.0 协议](./LICENSE)。
 

From 05ac71bac84c5d7f17197c7b03d44587bbac551f Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 16:45:49 +0800
Subject: [PATCH 69/95] Document

---
 images/panel-example2.png | Bin 0 -> 234161 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 images/panel-example2.png

diff --git a/images/panel-example2.png b/images/panel-example2.png
new file mode 100644
index 0000000000000000000000000000000000000000..c0116eb93be26ae1cf286a51b70957757de867ab
GIT binary patch
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HcmV?d00001


From a116d3db870de882238e65b9d48b12358cb3ea9c Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 16:46:10 +0800
Subject: [PATCH 70/95] useless example

---
 examples/data/datamodule.py | 35 -----------------------------------
 1 file changed, 35 deletions(-)
 delete mode 100644 examples/data/datamodule.py

diff --git a/examples/data/datamodule.py b/examples/data/datamodule.py
deleted file mode 100644
index 052e65e..0000000
--- a/examples/data/datamodule.py
+++ /dev/null
@@ -1,35 +0,0 @@
-from lumo import DataModule, ParamsType, TrainStage, DatasetBuilder
-import torch
-
-
-class MyDataModule(DataModule):
-    def idataloader(self, params: ParamsType = None, stage: TrainStage = None):
-        if stage.is_train():
-            print("init train dataloader")
-            db = (
-                DatasetBuilder()
-                    .add_input("xs", torch.rand(500, 28, 28))
-                    .add_input("ys", torch.randint(0, 10, (500,)))
-                    .add_output("xs", "xs")
-                    .add_output("ys", "ys")
-            )
-            loader = db.DataLoader(batch_size=10)
-        else:
-            print("init test dataloader")
-            db = (
-                DatasetBuilder()
-                    .add_input("xs", torch.rand(50, 28, 28))
-                    .add_input("ys", torch.randint(0, 10, (50,)))
-                    .add_output("xs", "xs")
-                    .add_output("ys", "ys")
-            )
-            loader = db.DataLoader(batch_size=10)
-        self.regist_dataloader_with_stage(stage, loader)
-
-
-dm = MyDataModule()
-print(dm._prop)
-print(len(dm.train_dataloader))
-print(dm._prop)
-print(len(dm.test_dataloader))
-print(dm._prop)

From 90aeb1bf75e046acb2945d8dc18c5ff19d521141 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 16:49:02 +0800
Subject: [PATCH 71/95] Document: panel image

---
 images/panel-example.png | Bin 0 -> 118724 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 images/panel-example.png

diff --git a/images/panel-example.png b/images/panel-example.png
new file mode 100644
index 0000000000000000000000000000000000000000..42f26f61ed14d686ec06aba68b1ba06914e711dd
GIT binary patch
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From 4428d9b182ae7ea0860c01eb3df21df0b0b5a27a Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 16:54:56 +0800
Subject: [PATCH 72/95] Panel: editor

---
 src/lumo/exp/lazy_panel.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index a035bf3..0c119c6 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -98,8 +98,8 @@ class ExceptionFormatter:
     'progress': None,
     'progress_': None,
     'exception': None,
-    'note': {'type': 'list', 'valuesLookup': True},
-    'tags': {'type': 'list', 'valuesLookup': True},
+    # 'note': {'type': 'list', 'valuesLookup': True},
+    # 'tags': {'type': 'list', 'valuesLookup': True},
 }
 
 

From 51017231bf6bca7fb87dddea3af6725023dc2b58 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 16:55:01 +0800
Subject: [PATCH 73/95] Document: update

---
 README.ch.md | 20 +++++++++++++++-----
 1 file changed, 15 insertions(+), 5 deletions(-)

diff --git a/README.ch.md b/README.ch.md
index 209904b..aeda8fe 100644
--- a/README.ch.md
+++ b/README.ch.md
@@ -51,23 +51,33 @@ pip install panel
 
 对已有项目，可以通过以下方式快速嵌入
 
+ - 引入
 ```python
 import random
 from lumo import SimpleExperiment, Params, Logger, Meter, Record
+```
 
+ - 初始化 Logger 和 Experiment
+```python
 logger = Logger()
 # 定义及使用，无需转换
 exp = SimpleExperiment(exp_name='my_exp_a')  # 为每种实验手动定义唯一名称
 exp.start()
 logger.add_log_dir(exp.mk_ipath())
+```
 
+ - 初始化参数
+```python
 # 替换基于 argparse 等的参数定义方法
 params = Params()
 params.dataset = params.choice('cifar10', 'cifar100')
 params.alpha = params.arange(default=1, left=0, right=10)
 params.from_args()  # python3 train.py --dataset=cifar100 --alpha=0.2
 print(params.to_dict())  # {"dataset": "cifar100", "alpha": 0.2}
+```
 
+ - 在训练过程中记录参数、存储信息
+```python
 # 记录实验参数
 exp.dump_info('params', params.to_dict())
 print(exp.test_name)  # 为每次实验自动分配唯一名称
@@ -111,10 +121,10 @@ exp.end()
 
 实验项目：
 
-| 项目                     | 说明                       |
-|------------------------|--------------------------|
-| [image-classification] | 集成了全监督、半监督、自监督的多个论文的复现代码 |
-| [emotion-recognition]  | 集成了情感分类、多模态情感分类的多个论文的复现代码 |
+| 项目                                                                                                        | 说明                            |
+|-----------------------------------------------------------------------------------------------------------|-------------------------------|
+| [image-classification](https://github.com/pytorch-lumo/image-classification)                              | 集成了全监督、半监督、自监督的多个论文的复现代码      |
+| [emotion-recognition-in-coversation](https://github.com/pytorch-lumo/emotion-recognition-in-conversation) | 集成了对话情感分类、多模态对话情感分类的多个论文的复现代码 |
 
 ## :small_orange_diamond: 可视化界面
 
@@ -131,7 +141,7 @@ widget.servable()
 
 ![Panel](./images/panel-example.png)
 
-将按手动条件过滤后的实验筛选出来：
+可视化手动筛选后的实验：
 ![Panel](./images/panel-example2.png)
 
 可以直接使用命令行打开页面查看当前所有实验：

From a384cff88d29ca50fd3c2768d384e81a6b8640b4 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 17:14:22 +0800
Subject: [PATCH 74/95] Document: update

---
 README.md | 205 ++++++++++++++++++++++++++----------------------------
 1 file changed, 97 insertions(+), 108 deletions(-)

diff --git a/README.md b/README.md
index 8d3e851..19836f7 100644
--- a/README.md
+++ b/README.md
@@ -1,3 +1,5 @@
+[中文](./README.ch.md)
+
 # lumo
 
 [![PyPI version](https://badge.fury.io/py/lumo.svg)](https://badge.fury.io/py/lumo)
@@ -5,162 +7,149 @@
 [![license](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/Lightning-AI/lightning/blob/master/LICENSE)
 ![Python-doc](./images/docstr_coverage_badge.svg)
 
-`lumo` is a light-weight library to help construct your experiment code, record your experiment results, especially in the field of deep learning.
-
-
-## Features
-
-`lumo` is designed for reducing difficulty of the frequent code modification in experiments and simplify the redundant code.
+`lumo` is a streamlined and efficient library that simplifies the management of all components required for experiments
+and focuses on enhancing the experience of deep learning practitioners.
 
-At present, `lumo` has these features:
+- **Experiment Management:** Allocates a unique path for each run, distinguishes and stores files for different types of
+  experiments, and manages code snapshots via Git.
+- **Parameter Management:** Provides more convenient parameter management than argparser based on fire.
+- **Runtime Configuration:** Provides configuration management under multi-level scopes.
+- **Visualization:** Provides an interactive Jupyter experiment management panel based
+  on [Panel](https://panel.holoviz.org/index.html).
+- Additional optimization for deep learning:
+    - **Training:** Provides easily extendable training logic based on Trainer and provides comprehensive callback logic.
+    - **Optimizer:** Integrated parameter and optimizer construction.
+    - **Data:** Abstraction of dataset construction process, combination of multiple DataLoaders, etc.
+    - **Distributed Training:** Also supports multiple training acceleration frameworks, unified abstraction, and easy
+      switching at any time.
+- More utilities...
 
- - Simplest code for **Hyperparameter Configuration**、**Dataset Building**、**Module Checkpoint**、**Meter and Log**.
- - Include Git support and random seed management. You can **reset** and **archive** and **reimplement your experiments** by using simple console command.
- - Include a **deep learning experiment code templete**. You can add any experiments with linearly increasing code complexity by using it.
- - The framework follows the design paradigm of **convention over configuration**, the more you follow the convention, the more the framework will do for you.
+# :book: Table of Contents
 
-> Better use Pycharm.
+- [Installation](#installation)
+- [Quick Start](#quick-start)
 
-See [document](https://sailist.github.io/lumo/) for details. 
+# :cloud: Installation
 
+Install the published and tested version:
 
-
-## Install
 ```bash
-pip install lumo
+pip install -U lumo
 ```
 
-or 
+Or install the latest version from the dev1 branch:
 
 ```bash
-git clone https://github.com/sailist/lumo
-
-python setup.py install
+pip install git+https://github.com/pytorch-lumo/lumo@dev1
 ```
 
-### test
+The experiment panel depends on Panel, which needs to be installed separately:
 
 ```
-python -m pytest # or python3 -m pytest
-```
-
-> Only a part of code have unit test.
-
-
-## Requirements
-
- - install lumo will automatically install three light other libraries: [fire](https://github.com/google/python-fire), [psutil](https://github.com/giampaolo/psutil), [joblib](https://github.com/joblib/joblib).
- - lumo has mandatory dependencies on `pytorch`, `pandas` and `numpy`, you should manully install these before using lumo since they are usually common-used.
- - lumo has an optional dependency on `GitPython` as a plugin to execute git command, you can run `pip install GitPython` to install it.
-
-```shell
-pip install pandas numpy GitPython
+pip install panel
 ```
-and then see [pytorch](https://pytorch.org/) to install torch. 
-
-
 
-## Introduction
+# :book: Quick Start
 
-Unlike other pytorch tools, `lumo` mainly designed for research, there are two core idea of it:
+Here are two classic scenarios:
 
-1. Reduce repetition of your code.
-2. Make all operations **recordable**, **resumable**, **analyzable**.
+## :small_orange_diamond: Embedding into Existing Projects
 
+For existing projects, you can quickly embed Lumo by following these steps:
 
-Your can click [Tutorial](https://sailist.github.io/lumo/tutorial/) to learn the basic use of this framework. After that, you can view [Cookbook](https://sailist.github.io/lumo/cookbook/) to see some details of this library.
+- Import Lumo and initialize Logger and Experiment:
 
-A suggested learning order may be：
-
- - Learn highly frequency used module: [Define hyperparameter(Params)](https://sailist.github.io/lumo/params)、[Record variable(Meter)](https://sailist.github.io/lumo/meter)、[Log(Logger)](/lumo/logger)、[Reshape your dataloader(DataBundler)](https://sailist.github.io/lumo/bundler) and their aggregation [Trainer](https://sailist.github.io/lumo/trainer).
- - Learn how to manage/analyse your experiment by [Config](https://sailist.github.io/lumo/exp) and [Experiment](https://sailist.github.io/lumo/exp)
- - Learn how to simple manage random seed by [RndManager](https://sailist.github.io/lumo/rnd) and to create your dataset elegantly by [DatasetBuilder](https://sailist.github.io/lumo/builder)
-
-After learning above contents, you can view [Cookbook](https://sailist.github.io/lumo/cookbook/) to learn the use of [tempelet code](https://sailist.github.io/lumo/structure) and other [details](https://sailist.github.io/lumo/details).
-
-You can also view another repository [lumo-implement](https://github.com/lumo/lumo-implement) to see a bigger example, it will continuously reimplement papers I interested by using the templete provided in `lumo`. 
+```python
+import random
+from lumo import SimpleExperiment, Params, Logger, Meter, Record
 
-## Examples
+logger = Logger()
+exp = SimpleExperiment(exp_name='my_exp_a')
+exp.start()
+logger.add_log_dir(exp.mk_ipath())
+```
 
-Before start, maybe you'd like to see some simple examples to learn what can `lumo` do.
+- Initialize parameters:
 
-### Define hyperparameters
-By use `lumo.frame.Params`, you can define hyperparameters simply. See [Params](https://sailist.github.io/lumo/params) for details.
-```python 
-from lumo import Params
+```python
 params = Params()
-params.batch_size = 128
-params.from_args() # from command args
-
->>> python ap.py --optim.lr=0.001 --epoch=400 --dataset=cifar10 --k=12
+params.dataset = params.choice('cifar10', 'cifar100')
+params.alpha = params.arange(default=1, left=0, right=10)
+params.from_args()  # python3 train.py --dataset=cifar100 --alpha=0.2
+print(params.to_dict())  # {"dataset": "cifar100", "alpha": 0.2}
 ```
-### Record variable
 
-By using `lumo.frame.Meter`, you can record variable and update its average value with as little code as possible. See [Meter](https://sailist.github.io/lumo/meter) for details.
+- Record parameters and store information during training:
 
 ```python
-from lumo import Meter,AvgMeter
-
-am = AvgMeter() # use for record average
-for j in range(500):
-    meter = Meter()
-    meter.percent(meter.c_) # when print, format 'c' as a percentage
-    meter.a = 1
-    meter.b = "2"
-    meter.c = torch.rand(1)[0]
-
-    meter.loss = loss_fn(...)
-    meter.rand = torch.rand(2)
-    meter.d = [4] # you can record any type of variable
-    meter.e = {5: "6"}
-
-    am.update(meter) # Update current value in meter. Average value will be calculated automatic by declaration and the type of the variable.
-    print(am)
-```
+exp.dump_info('params', params.to_dict())
+print(exp.test_name)
 
+params.to_yaml(exp.mk_ipath('params.yaml'))
 
-## Contribute
+for i in range(10):
+    max_acc = exp.dump_metric('Acc', random.random(), cmp='max')
+    logger.info(f'Max acc {max_acc}')
 
-`lumo` will be better in the future, but there are still some lack exists currently, including:
+    ckpt_fn = exp.mk_bpath('checkpoints', f'model_{i}.ckpt')
+    ...  # save code given ckpt_fn
 
- - **Lack of more detail guide** because of the lacking of developer's energy and time.
- - **Lack more tests**. unit test only covers a part of the code. I hope I fixed all bugs during my using of it, but there is no guarantee of it. The compatibility is also unguaranteed. So, welcome to [issus](https://github.com/sailist/lumo/issues) it if you find it.
- - **Lack of development experience**. So the version number may be confused.
+record = Record()
+for batch in range(10):
+    m = Meter()
+    m.mean.Lall = random.random()
+    m.last.lr = batch
+    record.record(m)
+    logger.info(record)
 
-Thanks for all contribution.
+exp.end()
+```
 
+## :small_orange_diamond: Building from Scratch
 
+If you want to start a new deep learning experiment from scratch, you can use Lumo to accelerate your code development.
+Below are examples of Lumo training at different scales:
 
-For file read/write and get/set, I designed
+one-fine training:
 
-- [Params], to make runtime config get/set/load/dump easily,
-- [globs], a global/local/runtime environment variables manager.
-- [Saver], to help you save/load/manage your checkpoints/models in one class.
+| Example                                     | CoLab | Lines of Code |
+|---------------------------------------------|-------|---------------|
+| [MNIST example](./examples/mnist.py)        |       | 118           |
+| [MocoV2 trains CIFAR10](./examples/moco.py) || 284   |
+| [Multi-GPU training ImageNet]()             |||
 
-For data processing, I designed
+Experimental project:
 
-- [Builder], to hold nearly all dataset formats and special operations by one class,
+| Project                                                                                                       | Description                            |
+|-----------------------------------------------------------------------------------------------------------|-------------------------------|
+| [image-classification](https://github.com/pytorch-lumo/image-classification)                              | Reproducible code for multiple papers with full supervision, semi-supervision, and self-supervision      |
+| [emotion-recognition-in-coversation](https://github.com/pytorch-lumo/emotion-recognition-in-conversation) | Reproducible code for multiple papers on dialogue emotion classification and multimodal dialogue emotion classification |
 
-For managing experiments, I designed
 
-- [Experiment], which can
-    - make you build a suitable directory and file path in one place,
-    - make you record lightweight data, and
-    - help you make snapshot for your project code (based on git), which can make each result recoverable and
-      reproducible
-- [random manager], a cross-lib(random/numpy/pytorch) random seed manager
+## :small_orange_diamond: Visual Interface
 
-For log and meter variables produced during experiment, I designed
+In jupyter:
 
-- [Meter] to meter every thing in appropriate format, and
-- [Logger] to log every thing in appropriate format.
+```python
+from lumo import Watcher
 
-Finally, I designed [Trainer] to bundle all module above for deep learning experiment.
+w = Watcher()
+df = w.load()
+widget = w.panel(df)
+widget.servable()
+```
 
+![Panel](./images/panel-example.png)
 
-As you can see, These modules covered most demandings on deeplearning 
+Manually filtered experiments for visualization:
+![Panel](./images/panel-example2.png)
 
-You can find what you want and click the link to quickly learn HOW TO USE it! All module is designed easy to use, it's
-my principles.
+You can directly use the command line:
+
+```
+lumo board [--port, --address, --open]
+```
 
+# :scroll: License
 
+Distributed under the GNU General Public License 3.0. See [LICENSE](./LICENSE) for more information.

From 106de763d3a18184722ab6256007f99b033fa61d Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 17:23:05 +0800
Subject: [PATCH 75/95] test: fix import

---
 tests/utils/test_io.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/utils/test_io.py b/tests/utils/test_io.py
index fc52be6..c45e8f2 100644
--- a/tests/utils/test_io.py
+++ b/tests/utils/test_io.py
@@ -1,6 +1,6 @@
 import yaml
 from lumo.utils.safe_io import *
-
+import os
 
 def test_dump_json(tmpdir):
     # Test that dump_json creates a valid JSON file

From e9c0cf70ece2d5b0ce9d1d2e79b7b08426d2636d Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 17:23:17 +0800
Subject: [PATCH 76/95] docstring

---
 src/lumo/core/interp.py | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/src/lumo/core/interp.py b/src/lumo/core/interp.py
index ad7a2c1..21334b8 100644
--- a/src/lumo/core/interp.py
+++ b/src/lumo/core/interp.py
@@ -281,7 +281,7 @@ def __call__(self, cur):
 
 
 class Cos(ABCContinuous):
-    """one cycle cosine functoin
+    r"""one cycle cosine functoin
 
       end ->         ,---------
                     /
@@ -309,7 +309,7 @@ def interp(cls, cur, start=0., end=1., left=0., right=1., *args, **kwargs):
 
 
 class Linear(ABCContinuous):
-    """linear schedule
+    r"""linear schedule
 
             ^
     end     |               .*
@@ -359,7 +359,7 @@ def interp(cls, cur, start=0., end=1., left=0., right=1., *args, **kwargs):
 
 
 class Log(ABCContinuous):
-    """
+    r"""
     quick to slow
 
      end   |                              *
@@ -395,7 +395,7 @@ def interp(cls, cur, start=0., end=1., left=0., right=1., *args, **kwargs):
 
 
 class Constant(ABCContinuous):
-    """
+    r"""
     A scheduler representing a constant value
                 |
     constant    |--------------
@@ -410,7 +410,7 @@ def __init__(self, value=0.5, *args, **kwargs):
 
 
 class PeriodCos(ABCPeriod):
-    """
+    r"""
     periodic cosine schedule
 
       end ->         ,-.     ,-.     ,-.     ,-.
@@ -432,7 +432,7 @@ def interp(cls, cur, start=0., end=1., left=0., period=1., *args, **kwargs):
 
 
 class PeriodHalfCos(ABCPeriod):
-    """
+    r"""
     half periodic cosine schedule, period is (right-left)
 
       end ->         ,-  ,-  ,-  ,-

From 29736789b1086dd226de9dce0654c10dc423d931 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 17:23:27 +0800
Subject: [PATCH 77/95] importing

---
 src/lumo/proc/dist.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/lumo/proc/dist.py b/src/lumo/proc/dist.py
index ad48d14..f0b2d7e 100644
--- a/src/lumo/proc/dist.py
+++ b/src/lumo/proc/dist.py
@@ -1,4 +1,5 @@
 import os
+import torch
 
 from torch import distributed as dist
 

From a687ca0df105d9ba2ec644f131d95023c214bbb6 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 17:23:43 +0800
Subject: [PATCH 78/95] update license

---
 README.ch.md | 2 +-
 README.md    | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.ch.md b/README.ch.md
index aeda8fe..f5f3333 100644
--- a/README.ch.md
+++ b/README.ch.md
@@ -158,5 +158,5 @@ lumo board [--port, --address, --open]
 
 # :scroll: License
 
-采用 [GNU General Public License 3.0 协议](./LICENSE)。
+采用 [Apache License Version 2.0](./LICENSE) 协议分发。
 
diff --git a/README.md b/README.md
index 19836f7..a4526c8 100644
--- a/README.md
+++ b/README.md
@@ -152,4 +152,4 @@ lumo board [--port, --address, --open]
 
 # :scroll: License
 
-Distributed under the GNU General Public License 3.0. See [LICENSE](./LICENSE) for more information.
+Distributed under the Apache License Version 2.0. See [LICENSE](./LICENSE) for more information.

From 2acddaa1edc652d6a84190ca72bcde53bc8823ab Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 17:23:51 +0800
Subject: [PATCH 79/95] importing

---
 setup.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/setup.py b/setup.py
index a0d9f4c..10eecd6 100644
--- a/setup.py
+++ b/setup.py
@@ -1,5 +1,4 @@
 import re
-from datetime import datetime
 from setuptools import setup, find_packages
 
 

From 0a79242c0600e2f8c06ffc40c0e8e172b02705f4 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Thu, 16 Mar 2023 20:43:25 +0800
Subject: [PATCH 80/95] script: and n and skip

---
 src/lumo/contrib/scan.py | 13 +++++++++++++
 1 file changed, 13 insertions(+)

diff --git a/src/lumo/contrib/scan.py b/src/lumo/contrib/scan.py
index 2155572..974fe70 100644
--- a/src/lumo/contrib/scan.py
+++ b/src/lumo/contrib/scan.py
@@ -19,6 +19,8 @@ def __init__(self):
         self.gpus = None
         self.group = None
         self.interval = 5  # sleep interval between two tests
+        self.skip = 0
+        self.n = -1
 
 
 def format_args(**kwargs):
@@ -49,7 +51,12 @@ def base_main(pm: ScanBaseParams, files: List[str], dics: List[dict]):
     gpus.append(None)
     gpus = cycle(gpus)
     c = 0
+    cnt = 0
     for i, (file, kwargs) in enumerate(zip(files, dics)):
+        if pm.skip > cnt:
+            cnt += 1
+            continue
+
         device = next(gpus)
         if device is None:
             # wait until all devices are free.
@@ -66,7 +73,13 @@ def base_main(pm: ScanBaseParams, files: List[str], dics: List[dict]):
             sleep=c * pm.interval,
             file=file, kwargs=format_args(**kwargs),
             device=device, group=group)
+
         c += 1
+        cnt += 1
         log.info(cur.strip())
         print(cur, flush=True, end='')
+
+        if pm.n > 0 and pm.skip + pm.n <= cnt:
+            break
+
     print('wait', flush=True)

From 6d03b43346d1c9bb1deae12443920b2c4801c48c Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 10:07:36 +0800
Subject: [PATCH 81/95] Experiment: backup

---
 src/lumo/{utils => contrib}/data/__init__.py  |   0
 .../data/augments/__init__.py                 |   0
 .../{utils => contrib}/data/augments/mix.py   |   0
 .../data/augments/transforms.py               |   0
 src/lumo/{utils => contrib}/data/splits.py    |   0
 src/lumo/exp/agent.py                         |   1 +
 src/lumo/exp/backup.py                        | 169 ++++++++++++++++++
 src/lumo/exp/experiment.py                    |   9 +-
 src/lumo/trainer/trainer.py                   |   5 +-
 9 files changed, 181 insertions(+), 3 deletions(-)
 rename src/lumo/{utils => contrib}/data/__init__.py (100%)
 rename src/lumo/{utils => contrib}/data/augments/__init__.py (100%)
 rename src/lumo/{utils => contrib}/data/augments/mix.py (100%)
 rename src/lumo/{utils => contrib}/data/augments/transforms.py (100%)
 rename src/lumo/{utils => contrib}/data/splits.py (100%)
 create mode 100644 src/lumo/exp/backup.py

diff --git a/src/lumo/utils/data/__init__.py b/src/lumo/contrib/data/__init__.py
similarity index 100%
rename from src/lumo/utils/data/__init__.py
rename to src/lumo/contrib/data/__init__.py
diff --git a/src/lumo/utils/data/augments/__init__.py b/src/lumo/contrib/data/augments/__init__.py
similarity index 100%
rename from src/lumo/utils/data/augments/__init__.py
rename to src/lumo/contrib/data/augments/__init__.py
diff --git a/src/lumo/utils/data/augments/mix.py b/src/lumo/contrib/data/augments/mix.py
similarity index 100%
rename from src/lumo/utils/data/augments/mix.py
rename to src/lumo/contrib/data/augments/mix.py
diff --git a/src/lumo/utils/data/augments/transforms.py b/src/lumo/contrib/data/augments/transforms.py
similarity index 100%
rename from src/lumo/utils/data/augments/transforms.py
rename to src/lumo/contrib/data/augments/transforms.py
diff --git a/src/lumo/utils/data/splits.py b/src/lumo/contrib/data/splits.py
similarity index 100%
rename from src/lumo/utils/data/splits.py
rename to src/lumo/contrib/data/splits.py
diff --git a/src/lumo/exp/agent.py b/src/lumo/exp/agent.py
index 2ccf33f..00f69d6 100644
--- a/src/lumo/exp/agent.py
+++ b/src/lumo/exp/agent.py
@@ -13,6 +13,7 @@
 
 
 def wait_pid_stop(info_dir=None):
+    """wait test """
     params = BaseParams()
     params.info_dir = info_dir
     params.from_args()
diff --git a/src/lumo/exp/backup.py b/src/lumo/exp/backup.py
new file mode 100644
index 0000000..35aea1c
--- /dev/null
+++ b/src/lumo/exp/backup.py
@@ -0,0 +1,169 @@
+from .experiment import Experiment
+import os
+from pprint import pformat
+from lumo.utils.fmt import strftime
+
+issue_title = """Test {test_name}"""
+
+summary_template = """
+{note}
+
+|Experiment Name|Test Name|Start| End |
+|---|---|---|---|
+|{exp_name}|{test_name}|{start}|{end}|
+
+```bash
+{command}
+```
+
+## Parameters
+```python
+{params}
+```
+
+## Metrics
+
+|Key|Value|
+|--|--|
+{metrics}
+
+Tensor metrics:
+```
+{non_scalar_metrics}
+```
+
+```
+{extra_info}
+```
+
+## Full properties
+<details>
+<summary> Click Here </summary>
+<code>
+{properties}
+</code>
+</details>
+"""
+
+
+def make_summary(exp: Experiment, **kwargs):
+    properties = exp.properties.copy()
+
+    execute = properties['execute']
+    params = properties.get('params', {})
+
+    metrics = {}
+    non_scalar_metrics = {}
+    for k, v in exp.metric.value.items():
+        if isinstance(v, (int, float)):
+            metrics[k] = f'{v:.5f}'
+        else:
+            non_scalar_metrics[k] = v
+    if len(metrics) == 0:
+        metrics['null'] = 'null'
+
+    progress = properties['progress']
+
+    # make markdown string
+    working_dir_str = execute['cwd']
+
+    common_prefix = os.path.commonprefix([execute['exec_argv'][0], execute['cwd']])
+    file = execute['exec_argv'][0][len(common_prefix):].lstrip('/')
+    bin = os.path.basename(execute['exec_bin'])
+    command_str = ' '.join(
+        [bin, file, *execute['exec_argv'][1:]])
+    params_str = pformat(params)
+    metrics_str = '\n'.join(f'|{k}|{v}|' for k, v in metrics.items())
+    non_scalar_metrics_str = '\n'.join(f'{k}\n{pformat(v)}\n' for k, v in non_scalar_metrics.items())
+    properties_str = pformat(properties)
+
+    start_str = progress.get('start', '')
+    end_str = progress.get('end', '')
+    extra_info_str = '\n'.join(f'{k}: {v}' for k, v in kwargs.items())
+
+    body = summary_template.format(
+        # working_dir=working_dir_str,
+        exp_name=exp.exp_name,
+        note=exp.load_note(),
+        test_name=exp.test_name,
+        start=start_str,
+        end=end_str,
+        # interval=interval_str,
+        extra_info=extra_info_str,
+        command=command_str,
+        params=params_str,
+        metrics=metrics_str,
+        non_scalar_metrics=non_scalar_metrics_str,
+        properties=properties_str,
+    )
+
+    username = os.getlogin()
+    home_with_name = os.path.expanduser('~')
+    body = body.replace(home_with_name, '~').replace(username, '{username}')
+
+    return body
+
+
+def backup_github_issue(exp: Experiment, repo: str, access_token: str,
+                        labels: list = None,
+                        **kwargs):
+    """backup ipath content and bpath content(optional) to github"""
+    try:
+        from github import Github
+    except ImportError as e:
+        raise ImportError('backup by github need PyGithub to be installed, try `pip install PyGithub`') from e
+
+    g = Github(login_or_token=access_token)
+    repo_obj = g.get_repo(repo)
+
+    title = issue_title.format(test_name=exp.test_name)
+
+    issue = repo_obj.create_issue(title=title)
+    exp.dump_info('backup', {strftime(): {'backend': 'github', 'number': issue.number, 'repo': repo}}, append=True)
+
+    body = make_summary(exp, **kwargs)
+
+    issue.edit(state='closed', body=body)
+    if labels is not None:
+        issue.edit(labels=labels)
+
+    return issue
+
+    # There is no way to upload files by GitHub Api
+    # filter backuped file sizes
+    # files = []
+    # for root, dirs, fs in os.walk(exp.mk_ipath()):
+    #     for f in fs:
+    #         absf = os.path.join(root, f)
+    #         file_size = os.path.getsize(absf) / (1024 * 1024)  # Mb
+    #         if file_size > size_limit:
+    #             continue
+    #         files.append(absf)
+    #
+    # for root, dirs, fs in os.walk(exp.mk_bpath()):
+    #     for f in fs:
+    #         absf = os.path.join(root, f)
+    #         file_size = os.path.getsize(absf) / (1024 * 1024)  # Mb
+    #         if file_size > size_limit:
+    #             continue
+    #         files.append(absf)
+
+    # repo.create_git_blob()
+    # {files}
+    # issue.create_comment()
+
+
+def backup_ssh(exp: Experiment, host, username, root, size_limit):
+    """compress backup zip files to target server with replacement"""
+    pass
+
+
+def backup_local(exp: Experiment, target):
+    pass
+
+
+backup_regist = {
+    'github': backup_github_issue,
+    'remote': backup_ssh,
+    'local': backup_local,
+}
diff --git a/src/lumo/exp/experiment.py b/src/lumo/exp/experiment.py
index 6367358..0e824f1 100644
--- a/src/lumo/exp/experiment.py
+++ b/src/lumo/exp/experiment.py
@@ -9,7 +9,7 @@
 import sys
 import time
 import traceback
-from typing import Any, List
+from typing import Any, List, overload
 from functools import wraps
 from lumo.decorators.process import call_on_main_process_wrap
 from lumo.proc import glob
@@ -906,6 +906,13 @@ def dict(self):
             'metrics': self.metric.value,
         }
 
+    def backup(self, backend: str = 'github', **kwargs):
+        from .backup import backup_regist
+        if backend == 'github':
+            kwargs.setdefault('access_token', glob['github_access_token'])
+
+        return backup_regist[backend](exp=self, **kwargs)
+
 
 class SimpleExperiment(Experiment):
     """
diff --git a/src/lumo/trainer/trainer.py b/src/lumo/trainer/trainer.py
index 6489f8a..c8307ff 100644
--- a/src/lumo/trainer/trainer.py
+++ b/src/lumo/trainer/trainer.py
@@ -63,7 +63,7 @@ def __init_subclass__(cls, **kwargs):
             raise TypeError(
                 f"Can't instantiate abstract class {cls.__name__} directly, please create a subclass of it.")
 
-    def __init__(self, params: ParamsType, dm: DataModule = None, accelerator='accelerator'):
+    def __init__(self, params: ParamsType, dm: DataModule = None, accelerator=None):
         if dm is None:
             dm = DataModule(params)
         else:
@@ -92,6 +92,7 @@ def __init__(self, params: ParamsType, dm: DataModule = None, accelerator='accel
         # self.accelerate = Accelerator(kwargs_handlers=[
         #     DistributedDataParallelKwargs(find_unused_parameters=params.get('find_unused_parameters', False))
         # ])
+        accelerator = glob.get('accelerator', 'accelerator')
         self.accelerate = get_accelerator(accelerator)
 
         self.accelerate.set_device(torch.device(device))
@@ -393,7 +394,7 @@ def device(self):
         Returns:
             The device used for training.
         """
-        return torch.device(self.params.device)
+        return self.accelerate.device
 
     def _load_fun_state_dict(self, src: dict):
         """

From f53cca53919876643640ac5e560f1807eae31cf3 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 10:16:15 +0800
Subject: [PATCH 82/95] Experiment: backup

---
 src/lumo/exp/backup.py | 11 +++++++++--
 1 file changed, 9 insertions(+), 2 deletions(-)

diff --git a/src/lumo/exp/backup.py b/src/lumo/exp/backup.py
index 35aea1c..e6e9b5a 100644
--- a/src/lumo/exp/backup.py
+++ b/src/lumo/exp/backup.py
@@ -2,6 +2,7 @@
 import os
 from pprint import pformat
 from lumo.utils.fmt import strftime
+import re
 
 issue_title = """Test {test_name}"""
 
@@ -97,9 +98,15 @@ def make_summary(exp: Experiment, **kwargs):
         properties=properties_str,
     )
 
-    username = os.getlogin()
+    try:
+        username = os.getlogin()
+    except OSError:
+        pass
+
+    # hide privacy path, only show relative path
     home_with_name = os.path.expanduser('~')
-    body = body.replace(home_with_name, '~').replace(username, '{username}')
+    body = re.sub("""'[^']*\.lumo""", '.lumo', body)
+    body = body.replace(home_with_name, '~')
 
     return body
 

From 15a089426a2a2896b04595d28e0d305593af685e Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 10:33:43 +0800
Subject: [PATCH 83/95] Experiment: backup

---
 src/lumo/exp/backup.py | 18 +++++++++++++++---
 1 file changed, 15 insertions(+), 3 deletions(-)

diff --git a/src/lumo/exp/backup.py b/src/lumo/exp/backup.py
index e6e9b5a..e131501 100644
--- a/src/lumo/exp/backup.py
+++ b/src/lumo/exp/backup.py
@@ -112,7 +112,7 @@ def make_summary(exp: Experiment, **kwargs):
 
 
 def backup_github_issue(exp: Experiment, repo: str, access_token: str,
-                        labels: list = None,
+                        labels: list = None, update: bool = True,
                         **kwargs):
     """backup ipath content and bpath content(optional) to github"""
     try:
@@ -125,8 +125,20 @@ def backup_github_issue(exp: Experiment, repo: str, access_token: str,
 
     title = issue_title.format(test_name=exp.test_name)
 
-    issue = repo_obj.create_issue(title=title)
-    exp.dump_info('backup', {strftime(): {'backend': 'github', 'number': issue.number, 'repo': repo}}, append=True)
+    issue = None
+    if update:
+        number = -1
+        old_backup = exp.properties.get('backup', {})
+        for k, v in sorted(list(old_backup.items())):
+            if v['backend'] == 'github' and v['repo'] == repo:
+                number = v['number']
+
+        if number > 0:
+            issue = repo_obj.get_issue(number)
+
+    if issue is None:
+        issue = repo_obj.create_issue(title=title)
+        exp.dump_info('backup', {strftime(): {'backend': 'github', 'number': issue.number, 'repo': repo}}, append=True)
 
     body = make_summary(exp, **kwargs)
 

From 407e8bb8c137de43df79e912b995df4da6b88aaf Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 11:28:41 +0800
Subject: [PATCH 84/95] Document

---
 README.ch.md             |  56 ++++++++++++++++++++++++++++++++++-----
 README.md                |  49 +++++++++++++++++++++++++++++++---
 images/backup_github.png | Bin 0 -> 146951 bytes
 3 files changed, 95 insertions(+), 10 deletions(-)
 create mode 100644 images/backup_github.png

diff --git a/README.ch.md b/README.ch.md
index f5f3333..d27b786 100644
--- a/README.ch.md
+++ b/README.ch.md
@@ -45,19 +45,21 @@ pip install panel
 
 # :book: 快速开始
 
-以下是两个经典场景：
+以下是几个经典场景：
 
 ## :small_orange_diamond: 已有项目嵌入
 
 对已有项目，可以通过以下方式快速嵌入
 
- - 引入
+- 引入
+
 ```python
 import random
 from lumo import SimpleExperiment, Params, Logger, Meter, Record
 ```
 
- - 初始化 Logger 和 Experiment
+- 初始化 Logger 和 Experiment
+
 ```python
 logger = Logger()
 # 定义及使用，无需转换
@@ -66,7 +68,8 @@ exp.start()
 logger.add_log_dir(exp.mk_ipath())
 ```
 
- - 初始化参数
+- 初始化参数
+
 ```python
 # 替换基于 argparse 等的参数定义方法
 params = Params()
@@ -76,7 +79,8 @@ params.from_args()  # python3 train.py --dataset=cifar100 --alpha=0.2
 print(params.to_dict())  # {"dataset": "cifar100", "alpha": 0.2}
 ```
 
- - 在训练过程中记录参数、存储信息
+- 在训练过程中记录参数、存储信息
+
 ```python
 # 记录实验参数
 exp.dump_info('params', params.to_dict())
@@ -150,11 +154,51 @@ widget.servable()
 lumo board [--port, --address, --open]
 ```
 
+## :small_orange_diamond: 复现实验
+
+对因为个中原因失败的实验，在藉由可视化界面观察并解决后，可以通过唯一实验 Id (test_name) 直接重跑，并对关键参数重新赋值：
+
+```
+lumo rerun 230313.030.57t --device=0
+```
+
+## :small_orange_diamond: 备份
+
+记录实验信息到 Github issue (基于 PyGitHub):
+
+```python
+from lumo import Experiment, Watcher
+from lumo import glob
+
+glob['github_access_token'] = 'ghp_*'  # `access_token` 的默认值，建议将 access_token 写在全局配置 `~/.lumorc.json` 中 
+
+w = Watcher()
+df = w.load()
+
+# 选择单个实验备份
+exp = Experiment.from_cache(df.iloc[0].to_dict())
+issue = exp.backup('github', repo='pytorch-lumo/image-classification-private',
+                   access_token='ghp_*',
+                   update=True,  # 如果已备份，则覆盖更新之前的 issue
+                   labels=None,  # 可选标签
+                   )
+print(issue.number)
+
+# 批量备份，并且基于每个实验的参数添加标签
+issues = df.apply(
+    lambda x: Experiment.from_cache(x.to_dict()).backup(..., labels=[x['params'].get('dataset', '')]),
+    axis=1
+)
+```
+
+![backup_github](./images/backup_github.png)
+
+
 # More
 
 # :pencil: Acknowledge
 
-从 2020 年维护至今。感谢 lumo 陪我见证我的学术生涯。
+从 2020 年维护至今。感谢 lumo 陪我见证我的研究生生涯。
 
 # :scroll: License
 
diff --git a/README.md b/README.md
index a4526c8..66fad59 100644
--- a/README.md
+++ b/README.md
@@ -17,7 +17,8 @@ and focuses on enhancing the experience of deep learning practitioners.
 - **Visualization:** Provides an interactive Jupyter experiment management panel based
   on [Panel](https://panel.holoviz.org/index.html).
 - Additional optimization for deep learning:
-    - **Training:** Provides easily extendable training logic based on Trainer and provides comprehensive callback logic.
+    - **Training:** Provides easily extendable training logic based on Trainer and provides comprehensive callback
+      logic.
     - **Optimizer:** Integrated parameter and optimizer construction.
     - **Data:** Abstraction of dataset construction process, combination of multiple DataLoaders, etc.
     - **Distributed Training:** Also supports multiple training acceleration frameworks, unified abstraction, and easy
@@ -115,8 +116,8 @@ one-fine training:
 | Example                                     | CoLab | Lines of Code |
 |---------------------------------------------|-------|---------------|
 | [MNIST example](./examples/mnist.py)        |       | 118           |
-| [MocoV2 trains CIFAR10](./examples/moco.py) || 284   |
-| [Multi-GPU training ImageNet]()             |||
+| [MocoV2 trains CIFAR10](./examples/moco.py) |       | 284   |
+| [Multi-GPU training ImageNet]()             |       ||
 
 Experimental project:
 
@@ -125,7 +126,6 @@ Experimental project:
 | [image-classification](https://github.com/pytorch-lumo/image-classification)                              | Reproducible code for multiple papers with full supervision, semi-supervision, and self-supervision      |
 | [emotion-recognition-in-coversation](https://github.com/pytorch-lumo/emotion-recognition-in-conversation) | Reproducible code for multiple papers on dialogue emotion classification and multimodal dialogue emotion classification |
 
-
 ## :small_orange_diamond: Visual Interface
 
 In jupyter:
@@ -150,6 +150,47 @@ You can directly use the command line:
 lumo board [--port, --address, --open]
 ```
 
+## :small_orange_diamond: re-run
+
+Experiment that failed due to certain reasons can be **re-run by using the unique experiment ID (test_name)** , extra
+parameters can be **reassigned and replaced**.
+
+```
+lumo rerun 230313.030.57t --device=0
+```
+
+## :small_orange_diamond: backup
+
+Backing up experiment information to a Github issue (based on PyGitHub):
+
+```python
+from lumo import Experiment, Watcher
+from lumo import glob
+
+glob[
+    'github_access_token'] = 'ghp_*'  # Default value for `access_token`. It is recommended to store the access_token in the global configuration `~/.lumorc.json`.
+
+w = Watcher()
+df = w.load()
+
+# Selecting a single experiment for backup
+exp = Experiment.from_cache(df.iloc[0].to_dict())
+issue = exp.backup('github', repo='pytorch-lumo/image-classification-private',
+                   access_token='ghp_*',
+                   update=True,  # If already backed up, overwrite the previous issue
+                   labels=None,  # Optional labels
+                   )
+print(issue.number)
+
+# Batch backup and add labels based on each experiment's parameters
+issues = df.apply(
+    lambda x: Experiment.from_cache(x.to_dict()).backup(..., labels=[x['params'].get('dataset', '')]),
+    axis=1
+)
+```
+
+![backup_github](./images/backup_github.png)
+
 # :scroll: License
 
 Distributed under the Apache License Version 2.0. See [LICENSE](./LICENSE) for more information.
diff --git a/images/backup_github.png b/images/backup_github.png
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HcmV?d00001


From 5a012ab10e88a676fcd5b71904850cff7b79479f Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 11:48:10 +0800
Subject: [PATCH 85/95] Document: update toc

---
 README.ch.md | 13 +++++++++++--
 README.md    | 12 +++++++++---
 2 files changed, 20 insertions(+), 5 deletions(-)

diff --git a/README.ch.md b/README.ch.md
index d27b786..bc0fe30 100644
--- a/README.ch.md
+++ b/README.ch.md
@@ -20,8 +20,17 @@
 
 # :book: 目录
 
-- [安装](#安装)
-- [快速开始](#快速开始)
+- :book: [目录](#book-目录)
+- :cloud: [安装](#cloud-安装)
+- :book: [快速开始](#book-快速开始)
+  - :small_orange_diamond: [已有项目嵌入](#small_orange_diamond-已有项目嵌入)
+  - :small_orange_diamond: [从零开始](#small_orange_diamond-从零开始)
+  - :small_orange_diamond: [可视化界面](#small_orange_diamond-可视化界面)
+  - :small_orange_diamond: [复现实验](#small_orange_diamond-复现实验)
+  - :small_orange_diamond: [备份](#small_orange_diamond-备份)
+- [More](#more)
+- :pencil: [Acknowledge](#pencil-acknowledge)
+- :scroll: [License](#scroll-license)
 
 # :cloud: 安装
 
diff --git a/README.md b/README.md
index 66fad59..6d48e02 100644
--- a/README.md
+++ b/README.md
@@ -27,9 +27,15 @@ and focuses on enhancing the experience of deep learning practitioners.
 
 # :book: Table of Contents
 
-- [Installation](#installation)
-- [Quick Start](#quick-start)
-
+- :cloud: [Installation](#cloud-installation)
+- :book: [Quick Start](#book-quick-start)
+  - :small_orange_diamond: [Embedding into Existing Projects](#small_orange_diamond-embedding-into-existing-projects)
+  - :small_orange_diamond: [Building from Scratch](#small_orange_diamond-building-from-scratch)
+  - :small_orange_diamond: [Visual Interface](#small_orange_diamond-visual-interface)
+  - :small_orange_diamond: [re-run](#small_orange_diamond-re-run)
+  - :small_orange_diamond: [backup](#small_orange_diamond-backup)
+- :scroll: [License](#scroll-license)
+- 
 # :cloud: Installation
 
 Install the published and tested version:

From 04d040adac9bb1774089de33a515283cf1a4c860 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 12:54:05 +0800
Subject: [PATCH 86/95] Document: update doc

---
 README.ch.md          |   2 ++
 README.md             |   4 +++-
 images/lumo-intro.png | Bin 0 -> 141062 bytes
 3 files changed, 5 insertions(+), 1 deletion(-)
 create mode 100644 images/lumo-intro.png

diff --git a/README.ch.md b/README.ch.md
index bc0fe30..a871874 100644
--- a/README.ch.md
+++ b/README.ch.md
@@ -18,6 +18,8 @@
     - 分布式训练：同样支持多种训练加速框架，统一抽象，方便随时切换
 - 更多工具类...
 
+![lumo-framework](./images/lumo-intro.png)
+
 # :book: 目录
 
 - :book: [目录](#book-目录)
diff --git a/README.md b/README.md
index 6d48e02..69993e8 100644
--- a/README.md
+++ b/README.md
@@ -25,6 +25,8 @@ and focuses on enhancing the experience of deep learning practitioners.
       switching at any time.
 - More utilities...
 
+![lumo-framework](./images/lumo-intro.png)
+
 # :book: Table of Contents
 
 - :cloud: [Installation](#cloud-installation)
@@ -35,7 +37,7 @@ and focuses on enhancing the experience of deep learning practitioners.
   - :small_orange_diamond: [re-run](#small_orange_diamond-re-run)
   - :small_orange_diamond: [backup](#small_orange_diamond-backup)
 - :scroll: [License](#scroll-license)
-- 
+
 # :cloud: Installation
 
 Install the published and tested version:
diff --git a/images/lumo-intro.png b/images/lumo-intro.png
new file mode 100644
index 0000000000000000000000000000000000000000..1199de271fa6f904e523cc885a338d92c3065c9b
GIT binary patch
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literal 0
HcmV?d00001


From e4d98f89dd2becd1601ac0c6de86a4ce645f6a66 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 13:16:35 +0800
Subject: [PATCH 87/95] docstr: add scripts

---
 docstr-coverage.sh | 9 +++++++++
 1 file changed, 9 insertions(+)
 create mode 100644 docstr-coverage.sh

diff --git a/docstr-coverage.sh b/docstr-coverage.sh
new file mode 100644
index 0000000..3d1a102
--- /dev/null
+++ b/docstr-coverage.sh
@@ -0,0 +1,9 @@
+docstr-coverage \
+  src/lumo/cli \
+  src/lumo/core \
+  src/lumo/data \
+  src/lumo/exp \
+  src/lumo/proc \
+  src/lumo/trainer \
+  src/lumo/utils
+

From 23742fba979736a9dcc69bceae2276ed48402405 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 13:16:51 +0800
Subject: [PATCH 88/95] docstr: docstr coverage upto 100%

---
 src/lumo/cli/__init__.py                |   1 +
 src/lumo/exp/backup.py                  |   4 +-
 src/lumo/exp/experiment.py              |   5 +
 src/lumo/exp/lazy_panel.py              |   6 +
 src/lumo/exp/watch.py                   |  33 ++--
 src/lumo/proc/dist.py                   |   9 ++
 src/lumo/proc/tz.py                     |   6 +
 src/lumo/trainer/accelerator.py         | 191 +++++++++++++++++++++++-
 src/lumo/trainer/backend/accelerator.py |  18 ++-
 src/lumo/utils/device.py                |   9 ++
 src/lumo/utils/safe_io.py               |   9 ++
 src/lumo/utils/subprocess.py            |  13 +-
 12 files changed, 271 insertions(+), 33 deletions(-)

diff --git a/src/lumo/cli/__init__.py b/src/lumo/cli/__init__.py
index 1a213d1..e9a39df 100644
--- a/src/lumo/cli/__init__.py
+++ b/src/lumo/cli/__init__.py
@@ -57,6 +57,7 @@ def board(port=11606, address=None, open=True):
 
 
 def main():
+    """the entry"""
     fire.Fire({
         'rerun': rerun,
         'note': note,
diff --git a/src/lumo/exp/backup.py b/src/lumo/exp/backup.py
index e131501..2ba86a7 100644
--- a/src/lumo/exp/backup.py
+++ b/src/lumo/exp/backup.py
@@ -48,6 +48,7 @@
 
 
 def make_summary(exp: Experiment, **kwargs):
+    """make a summary of experiment, can be used for backup or write report."""
     properties = exp.properties.copy()
 
     execute = properties['execute']
@@ -177,7 +178,8 @@ def backup_ssh(exp: Experiment, host, username, root, size_limit):
     pass
 
 
-def backup_local(exp: Experiment, target):
+def backup_local(exp: Experiment, target: str):
+    """backup in local dist"""
     pass
 
 
diff --git a/src/lumo/exp/experiment.py b/src/lumo/exp/experiment.py
index 0e824f1..0e128a9 100644
--- a/src/lumo/exp/experiment.py
+++ b/src/lumo/exp/experiment.py
@@ -374,6 +374,7 @@ def exec_argv(self):
             return []
 
     def trigger(self):
+        """trigger the disk change"""
         pass
 
     def _trigger_change(self, func):
@@ -907,6 +908,10 @@ def dict(self):
         }
 
     def backup(self, backend: str = 'github', **kwargs):
+        """
+        Backup this experiment into the given target, currently only support GitHub, you can implement your own way
+        by the provided information of Experiment.
+        """
         from .backup import backup_regist
         if backend == 'github':
             kwargs.setdefault('access_token', glob['github_access_token'])
diff --git a/src/lumo/exp/lazy_panel.py b/src/lumo/exp/lazy_panel.py
index 0c119c6..7fe49ae 100644
--- a/src/lumo/exp/lazy_panel.py
+++ b/src/lumo/exp/lazy_panel.py
@@ -45,6 +45,7 @@
 
 
 def FoldDictFormatter(column_name):
+    """unfold dict in summary tag"""
     base_template = """
     <details style="overflow: visible;">
         <summary>{column_name}</summary>
@@ -56,6 +57,7 @@ def FoldDictFormatter(column_name):
 
 
 def DictFormatter(column_name):
+    """unfold dict in list tag"""
     base_template = """
         <% _.each(value, function(vv, key) { %>
             <li><b><%= key %>:</b> <%= vv %></li>
@@ -65,6 +67,7 @@ def DictFormatter(column_name):
 
 
 class ExceptionFormatter:
+    """format exception"""
     base_template = """
 <details style="overflow: visible;">
     <summary> 
@@ -104,6 +107,7 @@ class ExceptionFormatter:
 
 
 def drop_nonscalar_metric(dic):
+    """only keep scalar metrics"""
     if not isinstance(dic, dict):
         return
 
@@ -114,6 +118,7 @@ def drop_nonscalar_metric(dic):
 
 
 def reformat_progress(dic):
+    """make progress"""
     if not isinstance(dic, dict):
         return {
             'ratio': '100%',
@@ -202,6 +207,7 @@ def make_experiment_tabular(df: pd.DataFrame):
     df = df[top_columns + list(extra_columns)]
 
     def on_cell_change(e: TableEditEvent):
+        """on edit cell"""
         nonlocal df
 
         if e.column == 'note':
diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index 97950f3..6f0a0ee 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -1,23 +1,3 @@
-"""
-Watcher 可以在运行实验后在 jupyter 或者网页上展示正在运行和已经运行结束的实验（按时间顺序？）
-以及可以简化记录实验的烦恼
-
-现在的核心痛点是
- - [ ] 所有元信息都有了，但是找不到哪个实验是哪个实验
- - [ ] 同时跑的多个实验有一个失败了，重跑时会混淆，或许需要一种覆盖手段 ->
- - > 怎么 rerun？
-        lumo rerun test_name √
-        lumo note html （用 streamlit 之类的生成动态网页）
-        lumo note cmd  (类似 top 的视角，按时间顺序排列)
-- > rerun 将已经跑的实验 move
-
-可以代替 analysis 的作用。主要有
-
--> 按照 progress 目录，获取所有的实验
--> 根据获取的实验，按顺序记录
--> 每次只记录
-
-"""
 import numbers
 import os
 import os.path
@@ -253,6 +233,7 @@ def mask(self, df):
         return mapping[self.op](value, self.value)
 
     def capply(self, df):
+        """apply operations in column axis"""
         import pandas as pd
         df = df.reset_index(drop=True)
         if self.op == 'drop_column':
@@ -322,8 +303,13 @@ def __init__(self, exp_root=None, hb_root=None, pid_root=None, db_root=None):
         self.hb_root = hb_root
         self.pid_root = pid_root
 
-    def retrieve(self, test_name=None):
-        raise NotImplementedError()
+    def retrieve(self, test_name=None) -> Experiment:
+        """retrieve the Experiment of given test name"""
+        df = self.load()
+        res = df[df['test_name'] == test_name]
+        if len(res) > 0:
+            return Experiment.from_cache(res.iloc[0].to_dict())
+        return None
 
     def update(self):
         """Diff & Update"""
@@ -357,6 +343,7 @@ def update(self):
         return updates
 
     def fullupdate(self):
+        """re-update all experiment from original experiment directories"""
         updates = {}
         for root, dirs, fs in os.walk(self.exp_root):
             for f in dirs:
@@ -398,6 +385,7 @@ def load(self, with_pandas=True):
         updates = self.update()
 
         def valid_row(dic):
+            """is a valid row?"""
             return isinstance(dic, dict) and 'test_name' in dic
 
         for dic_fn in os.listdir(self.db_root):
@@ -473,6 +461,7 @@ def server(self):
         pass
 
     def panel(self, df=None):
+        """create a dashboard powered by Panel, need to install panel library first."""
         from .lazy_panel import make_experiment_tabular
         if df is None:
             df = self.load()
diff --git a/src/lumo/proc/dist.py b/src/lumo/proc/dist.py
index f0b2d7e..3003019 100644
--- a/src/lumo/proc/dist.py
+++ b/src/lumo/proc/dist.py
@@ -79,6 +79,15 @@ def is_main():
 
 
 def gather(tensor):
+    """
+    Gather the tensor data across all processes in the distributed setting.
+
+    Args:
+        tensor (torch.Tensor): The tensor to be gathered.
+
+    Returns:
+        The gathered tensor data.
+    """
     if dist.is_initialized():
         if tensor.ndim == 0:
             tensor = tensor.clone()[None]
diff --git a/src/lumo/proc/tz.py b/src/lumo/proc/tz.py
index fb89bec..d3eb7d7 100644
--- a/src/lumo/proc/tz.py
+++ b/src/lumo/proc/tz.py
@@ -3,4 +3,10 @@
 
 
 def timezone():
+    """
+    Get the timezone from the global configuration, or default to 'Asia/Shanghai'.
+
+    Returns:
+        The timezone.
+    """
     return pytz.timezone(glob.get('timezone', 'Asia/Shanghai'))
diff --git a/src/lumo/trainer/accelerator.py b/src/lumo/trainer/accelerator.py
index c7e873f..72de399 100644
--- a/src/lumo/trainer/accelerator.py
+++ b/src/lumo/trainer/accelerator.py
@@ -8,30 +8,106 @@
 
 
 class Accelerator:
+    """
+    A class to define the interface for various types of accelerator.
+
+    Attributes:
+        _prop (dict): A dictionary of keyword arguments.
+
+    Methods:
+        device: A property method to get the device.
+        set_device: A method to set the device.
+        prepare_data_loader: A method to prepare the data loader.
+        prepare_model: A method to prepare the model.
+        prepare_optimizer: A method to prepare the optimizer.
+        unwrap_model: A method to unwrap the model.
+        prepare: A method to prepare the inputs for training.
+        wait_for_everyone: A method to wait for all processes to synchronize.
+        gather: A method to gather the tensor data.
+        backward: A method to compute the gradients using backpropagation.
+    """
+
     def __init__(self, **kwargs):
+        """
+        Initialize the class with a dictionary of keyword arguments.
+        """
         self._prop = kwargs
 
     @property
-    def device(self):
+    def device(self) -> torch.device:
+        """
+        Get the device.
+        """
         return self._prop.get('device', None)
 
-    def set_device(self, device):
+    def set_device(self, device: torch.device):
+        """
+        Set the device.
+
+        Args:
+            device (torch.device): The device to be set.
+        """
         assert isinstance(device, torch.device)
         self._prop['device'] = device
 
     def prepare_data_loader(self, dataloader):
+        """
+        Prepare the data loader.
+
+        Args:
+            dataloader: The data loader.
+
+        Returns:
+            The prepared data loader.
+        """
         return dataloader
 
     def prepare_model(self, model: torch.nn.Module):
+        """
+        Prepare the model.
+
+        Args:
+            model (torch.nn.Module): The model.
+
+        Returns:
+            The prepared model.
+        """
         return model.to(self.device)
 
     def prepare_optimizer(self, optimizer: torch.optim.Optimizer):
+        """
+        Prepare the optimizer.
+
+        Args:
+            optimizer (torch.optim.Optimizer): The optimizer.
+
+        Returns:
+            The prepared optimizer.
+        """
         return optimizer
 
     def unwrap_model(self, model):
+        """
+        Unwrap the model.
+
+        Args:
+            model: The model.
+
+        Returns:
+            The unwrapped model.
+        """
         return model
 
     def prepare(self, *args):
+        """
+        Prepare the inputs for training.
+
+        Args:
+            *args: The inputs.
+
+        Returns:
+            The prepared inputs.
+        """
         res = []
         for item in args:
             if isinstance(item, nn.Module):
@@ -45,31 +121,84 @@ def prepare(self, *args):
         return res
 
     def wait_for_everyone(self):
+        """
+        Wait for all processes to synchronize.
+        """
         torch.distributed.barrier()
 
     def gather(self, tensor: torch.Tensor):
+        """
+        Gather the tensor data.
+
+        Args:
+            tensor (torch.Tensor): The tensor to be gathered.
+
+        Returns:
+            The gathered tensor data.
+        """
         return gather(tensor)
 
     def backward(self, loss: torch.Tensor, **kwargs):
-        loss.backward(**kwargs)
+        """
+        Compute the gradients using backpropagation.
 
+        Args:
+            loss (torch.Tensor): The loss tensor.
+            **kwargs: The additional keyword arguments.
+        """
+        loss.backward(**kwargs)
 
 class HugAccelerator(Accelerator):
+    """
+    A class to define the interface for Hugging Face accelerator.
+
+    Methods:
+        set_device: A method to set the device.
+        prepare_data_loader: A method to prepare the data loader.
+        prepare_model: A method to prepare the model.
+        prepare_optimizer: A method to prepare the optimizer.
+        unwrap_model: A method to unwrap the model.
+        prepare: A method to prepare the inputs for training.
+        wait_for_everyone: A method to wait for all processes to synchronize.
+        gather: A method to gather the tensor data.
+        backward: A method to compute the gradients using backpropagation.
+    """
 
     def __init__(self, **kwargs):
+        """
+        Initialize the class with a dictionary of keyword arguments.
+        """
         super().__init__(**kwargs)
         from .backend.accelerator import Accelerator
         self._backbone = Accelerator()
 
     @property
     def device(self):
+        """
+        Get the device.
+        """
         return self._backbone.device
 
     def set_device(self, device: torch.device):
+        """
+        Set the device.
+
+        Args:
+            device (torch.device): The device to be set.
+        """
         assert isinstance(device, torch.device)
         self._backbone.state.device = device
 
     def prepare_data_loader(self, loader):
+        """
+        Prepare the data loader.
+
+        Args:
+            loader: The data loader.
+
+        Returns:
+            The prepared data loader.
+        """
         from accelerate.data_loader import DataLoaderShard, DataLoaderDispatcher
         if isinstance(loader, (DataLoaderShard, DataLoaderDispatcher)):
             warnings.warn('Duplicated prepare a same DataLoader twice, check your code.')
@@ -77,24 +206,79 @@ def prepare_data_loader(self, loader):
         return self._backbone.prepare_data_loader(loader)
 
     def prepare_model(self, model):
+        """
+        Prepare the model.
+
+        Args:
+            model: The model.
+
+        Returns:
+            The prepared model.
+        """
         return self._backbone.prepare_model(model)
 
     def prepare_optimizer(self, optimizer):
+        """
+        Prepare the optimizer.
+
+        Args:
+            optimizer: The optimizer.
+
+        Returns:
+            The prepared optimizer.
+        """
         return self._backbone.prepare_optimizer(optimizer)
 
     def unwrap_model(self, model):
+        """
+        Unwrap the model.
+
+        Args:
+            model: The model.
+
+        Returns:
+            The unwrapped model.
+        """
         return self._backbone.unwrap_model(model)
 
     def prepare(self, *args):
+        """
+        Prepare the inputs for training.
+
+        Args:
+            *args: The inputs.
+
+        Returns:
+            The prepared inputs.
+        """
         return self._backbone.prepare(*args)
 
     def wait_for_everyone(self):
+        """
+        Wait for all processes to synchronize.
+        """
         self._backbone.wait_for_everyone()
 
     def gather(self, tensor):
+        """
+        Gather the tensor data.
+
+        Args:
+            tensor: The tensor to be gathered.
+
+        Returns:
+            The gathered tensor data.
+        """
         return self._backbone.gather(tensor)
 
     def backward(self, loss: torch.Tensor, **kwargs):
+        """
+        Compute the gradients using backpropagation.
+
+        Args:
+            loss (torch.Tensor): The loss tensor.
+            **kwargs: The additional keyword arguments.
+        """
         self._backbone.backward(loss, **kwargs)
 
 
@@ -108,5 +292,6 @@ def backward(self, loss: torch.Tensor, **kwargs):
 
 
 def get_accelerator(name: str, **kwargs) -> Accelerator:
+    """Get the accelerator for the specified name."""
     assert name in register, ', '.join(register.keys())
     return register[name](**kwargs)
diff --git a/src/lumo/trainer/backend/accelerator.py b/src/lumo/trainer/backend/accelerator.py
index 488e539..5c64a75 100644
--- a/src/lumo/trainer/backend/accelerator.py
+++ b/src/lumo/trainer/backend/accelerator.py
@@ -4,13 +4,23 @@
 
 class Accelerator(_Accelerator):
     """
-    Accelerator instance for distributed training (on multi-GPU, TPU) or mixed precision training.
+     Accelerator instance for distributed training (on multi-GPU, TPU) or mixed precision training.
 
-    This Accelerator subclass is use for `Trainer`, the only difference is that
-    the device of data will be controlled by Trainer rather than Accelerator.
-    """
+     This Accelerator subclass is used for `Trainer`. The only difference is that
+     the device of data will be controlled by `Trainer` rather than `Accelerator`.
+     """
 
     def prepare_data_loader(self, data_loader, **kwargs):
+        """
+        Prepare the data loader.
+
+        Args:
+            data_loader: The data loader.
+            **kwargs: Additional keyword arguments.
+
+        Returns:
+            The prepared data loader.
+        """
         return prepare_data_loader(
             data_loader,
             None,  # None instead of self.device,
diff --git a/src/lumo/utils/device.py b/src/lumo/utils/device.py
index 2e49881..ef6ee94 100644
--- a/src/lumo/utils/device.py
+++ b/src/lumo/utils/device.py
@@ -14,6 +14,15 @@ def honor_type(obj, generator):
 
 
 def is_torch_tensor(tensor):
+    """
+    Check if the input is a PyTorch tensor.
+
+    Args:
+        tensor: The input tensor.
+
+    Returns:
+        A boolean indicating if the input is a PyTorch tensor.
+    """
     return isinstance(tensor, torch.Tensor)
 
 
diff --git a/src/lumo/utils/safe_io.py b/src/lumo/utils/safe_io.py
index 0daffc7..064404c 100644
--- a/src/lumo/utils/safe_io.py
+++ b/src/lumo/utils/safe_io.py
@@ -17,6 +17,15 @@
 
 
 def filter_unserializable_values(dic):
+    """
+    Recursively filter out unserializable values in a dictionary.
+
+    Args:
+        dic (dict): The dictionary to be filtered.
+
+    Returns:
+        The filtered dictionary.
+    """
     for key, value in list(dic.items()):
         if isinstance(value, dict):
             filter_unserializable_values(value)
diff --git a/src/lumo/utils/subprocess.py b/src/lumo/utils/subprocess.py
index 749a793..ee456e1 100644
--- a/src/lumo/utils/subprocess.py
+++ b/src/lumo/utils/subprocess.py
@@ -5,6 +5,12 @@
 
 
 def consume(p: subprocess.Popen):
+    """
+    Consume the standard output and standard error of the specified process.
+
+    Args:
+        p (subprocess.Popen): The process to consume the output from.
+    """
     for stream in [p.stdout, p.stderr]:
         while True:
             line = stream.readline().decode('utf-8')
@@ -18,9 +24,10 @@ def run_command(command: str, cwd=None, env=None, non_block=False):
     Executes a command in the shell and captures its standard output and standard error.
 
     Args:
-        command: a string representing the command to execute in the shell.
-        cwd: a string representing the working directory to execute the command in. Default is None.
-        env: a dictionary representing the environment variables to set for the command. Default is None.
+        command (str): A string representing the command to execute in the shell.
+        cwd (str): A string representing the working directory to execute the command in. Default is None.
+        env (dict): A dictionary representing the environment variables to set for the command. Default is None.
+        non_block (bool): A flag to indicate whether to run the command in a non-blocking manner. Default is False.
 
     Returns:
         The return code of the executed command.

From 65afefc4f34d79df397373ed34c392fb0c33dd07 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 14:10:54 +0800
Subject: [PATCH 89/95] test: coverage upto 77%

---
 tests/exp/test_condition.py | 49 +++++++++++++++++++++++++++++++++++++
 1 file changed, 49 insertions(+)
 create mode 100644 tests/exp/test_condition.py

diff --git a/tests/exp/test_condition.py b/tests/exp/test_condition.py
new file mode 100644
index 0000000..81d830c
--- /dev/null
+++ b/tests/exp/test_condition.py
@@ -0,0 +1,49 @@
+import pandas as pd
+from lumo import C
+
+# create a sample DataFrame
+data = {'name': ['Alice', 'Bob', 'Charlie', 'David', 'Emily'],
+        'age': [25, 30, 35, 40, 45],
+        'city': [{'index': 0}, {'index': 1}, {'index': 2}, {'index': 3}, {'index': 4}]}
+df = pd.DataFrame(data)
+
+
+def test_row_filter():
+    # create and apply the condition to filter the DataFrame
+    filtered_df = (C['age'] >= 35).apply(df)
+    # assert that only the rows with age >= 35 are in the filtered DataFrame
+    assert filtered_df.shape == (3, 3)
+    assert filtered_df['age'].min() >= 35
+
+
+def test_column_edit_add():
+    # test the column edit operation C+{'city.index':'cindex'}
+    assert (C + {'city.index': 'cindex'}).op == 'add_column'
+    new_df = (C + {'city.index': 'cindex'}).apply(df)
+    assert 'cindex' in new_df.columns
+    assert new_df.columns.tolist() == ['name', 'age', 'city', 'cindex']
+
+    # test the column edit operation C-['city']
+    new_df = (C - ['city']).apply(df)
+    assert 'city' not in new_df.columns
+    assert new_df.columns.tolist() == ['name', 'age']
+
+    # test the column edit operation C-['city','name']
+    new_df = (C - ['city', 'name']).apply(df)
+    assert 'city' not in new_df.columns
+    assert 'name' not in new_df.columns
+    assert new_df.columns.tolist() == ['age']
+
+
+def test_pipeline():
+    # test the pipeline operation
+    filtered_df = C.pipe(df, [
+        (C['age'] > 35),
+        C + {'city.index': 'cindex'},
+        C - ['city', 'name']
+    ])
+    assert filtered_df.shape == (2, 2)
+    assert 'name' not in filtered_df.columns
+    assert 'city' not in filtered_df.columns
+    assert 'age' in filtered_df.columns
+    assert 'cindex' in filtered_df.columns

From 2f0a3f1b9643f1f6a169c95b1442a7ebcbc12850 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 14:11:10 +0800
Subject: [PATCH 90/95] docstring: fix examples

---
 src/lumo/exp/watch.py | 34 +++++++++++++++++++---------------
 1 file changed, 19 insertions(+), 15 deletions(-)

diff --git a/src/lumo/exp/watch.py b/src/lumo/exp/watch.py
index 6f0a0ee..d853dbf 100644
--- a/src/lumo/exp/watch.py
+++ b/src/lumo/exp/watch.py
@@ -69,7 +69,7 @@ class Condition:
     # create a sample DataFrame
     data = {'name': ['Alice', 'Bob', 'Charlie', 'David', 'Emily'],
             'age': [25, 30, 35, 40, 45],
-            'city': ['New York', 'Los Angeles', 'Chicago', 'Houston', 'Miami']}
+            'city': [{'index':0}, {'index':1}, {'index':2},{'index':3},{'index':4}]}
     df = pd.DataFrame(data)
 
     # create and apply the condition to filter the DataFrame
@@ -117,32 +117,34 @@ def __getitem__(self, item):
         return Condition(item)
 
     def __add__(self, other):
-        self.op = 'add_column'
-        self.value = {}
-        self.op
+        c = Condition()
+        c.op = 'add_column'
+        c.value = {}
         if isinstance(other, str):
-            self.value[other] = other
+            c.value[other] = other
         elif isinstance(other, dict):
-            self.value.update(other)
+            c.value.update(other)
         else:
             raise NotImplementedError()
-        return self
+        return c
 
     def __sub__(self, other):
-        self.name = None
-        self.op = 'drop_column'
-        self.value = {}
+        c = Condition()
+        c.name = None
+        c.op = 'drop_column'
+        c.value = {}
         if isinstance(other, str):
-            self.value.update({other: None})
+            c.value.update({other: None})
         elif isinstance(other, (list, set, dict)):
-            self.value.update({k: None for k in other})
+            c.value.update({k: None for k in other})
         else:
             raise NotImplementedError()
-        return self
+        return c
 
     def __neg__(self):
-        self.op = 'drop_column'
-        return self
+        c = Condition()
+        c.op = 'drop_column'
+        return c
 
     def __ge__(self, other):
         if other is None:
@@ -243,6 +245,8 @@ def capply(self, df):
                 var = [self.value]
             else:
                 var = list(self.value)
+            print(var)
+            print(df.columns)
             df = df.drop(var, axis=1)
         else:
             assert isinstance(self.value, dict)

From a601b5be700458b74a7ce2cf9ab55cc69f9a1837 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 14:11:25 +0800
Subject: [PATCH 91/95] =?UTF-8?q?Document=EF=BC=9A=20update=20content?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 README.ch.md | 57 ++++++++++++++++++++++++++++++++++++++-
 README.md    | 76 +++++++++++++++++++++++++++++++++++++++++++++-------
 2 files changed, 123 insertions(+), 10 deletions(-)

diff --git a/README.ch.md b/README.ch.md
index a871874..abf21da 100644
--- a/README.ch.md
+++ b/README.ch.md
@@ -7,7 +7,7 @@
 
 `lumo` 是一个精简高效的库，简化了实验所需的所有组件的管理，并特别关注增强深度学习实践者的体验。
 
-- 实验管理：: 为每次运行分配唯一路径，区分不同类型的文件并存储；并通过 git 管理代码快照。
+- 实验管理：: 为每次运行分配唯一路径，区分不同类型的文件并存储；通过 git 管理代码快照；记录实验中产生的一切信息，保障可回溯、可复现
 - 参数管理：基于 fire 提供比 argparser 更便捷的参数管理
 - 运行时配置：提供多级作用域下的配置管理
 - 可视化：基于 [Panel](https://panel.holoviz.org/index.html) 提供可交互的 jupyter 实验管理面板
@@ -204,6 +204,61 @@ issues = df.apply(
 
 ![backup_github](./images/backup_github.png)
 
+Full properties 内容:
+```
+{'agent': nan,
+ 'backup': {'23-03-17-003438': {'backend': 'github',
+                                'number': 9,
+                                'repo': '...'},
+            },
+ 'exception': nan,
+ 'execute': {'cwd': '~/Documents/Python/lumo',
+             'exec_argv': ['~/Documents/Python/lumo/a.py'],
+             'exec_bin': '~/.pyenv/versions/3.9.16/bin/python3.9',
+             'exec_file': '~/Documents/Python/lumo/a.py',
+             'repo': '~/Documents/Python/lumo'},
+ 'exp_name': 'my_exp_a',
+ 'git': {'commit': '1014b6b5',
+         'dep_hash': 'c93b8c4e340882f55cf0c8e125fa0203',
+         'repo': '~/Documents/Python/lumo'},
+ 'hooks': {'Diary': {'loaded': True, 'msg': ''},
+           'FinalReport': {'loaded': True, 'msg': ''},
+           'GitCommit': {'loaded': True, 'msg': ''},
+           'LastCmd': {'loaded': True, 'msg': ''},
+           'LockFile': {'loaded': True, 'msg': ''},
+           'RecordAbort': {'loaded': True, 'msg': ''}},
+ 'lock': {'accelerate': '0.16.0',
+          'decorator': '5.1.1',
+          'fire': '0.5.0',
+          'hydra': '1.3.2',
+          'joblib': '1.2.0',
+          'lumo': '0.15.0',
+          'numpy': '1.24.2',
+          'omegaconf': '2.3.0',
+          'psutil': '5.9.4',
+          'torch': '1.13.1'},
+ 'note': 'This is a Note',
+ 'params': {'alpha': 1, 'dataset': 'cifar10'},
+ 'paths': {'blob_root': '~/.lumo/blob',
+           'cache_root': '~/.lumo/cache',
+           'info_root': '~/.lumo/experiments'},
+ 'pinfo': {'hash': '0af4b77497c85bc5b65ccbdd9ff4ca0f',
+           'obj': {'argv': ['~/.pyenv/versions/3.9.16/bin/python3.9',
+                            '~/Documents/Python/lumo/a.py'],
+                   'pid': 63975,
+                   'pname': 'python3.9',
+                   'pstart': 1678898740.099484},
+           'pid': 63975},
+ 'progress': {'end': '23-03-16-004542',
+              'end_code': 0,
+              'last_edit_time': '23-03-16-004542',
+              'ratio': 1,
+              'start': '23-03-16-004542',
+              'update_from': None},
+ 'tags': [],
+ 'test_name': '230316.000.8ct',
+ 'trainer': nan}
+```
 
 # More
 
diff --git a/README.md b/README.md
index 69993e8..7ac0c42 100644
--- a/README.md
+++ b/README.md
@@ -10,11 +10,12 @@
 `lumo` is a streamlined and efficient library that simplifies the management of all components required for experiments
 and focuses on enhancing the experience of deep learning practitioners.
 
-- **Experiment Management:** Allocates a unique path for each run, distinguishes and stores files for different types of
-  experiments, and manages code snapshots via Git.
-- **Parameter Management:** Provides more convenient parameter management than argparser based on fire.
+- **Experimental Management**: **Assign unique id and path** for each run, distinguish and store various file types;
+  manage **code snapshots** through git; **record all information** generated during the experiment to ensure
+  traceability and reproducibility.
+- **Parameter Management:** Provides more convenient **parameter management** than argparser based on fire.
 - **Runtime Configuration:** Provides configuration management under multi-level scopes.
-- **Visualization:** Provides an interactive Jupyter experiment management panel based
+- **Visualization:** Provides an Jupyter-compatible interactive dashboard for experiment management based
   on [Panel](https://panel.holoviz.org/index.html).
 - Additional optimization for deep learning:
     - **Training:** Provides easily extendable training logic based on Trainer and provides comprehensive callback
@@ -31,11 +32,11 @@ and focuses on enhancing the experience of deep learning practitioners.
 
 - :cloud: [Installation](#cloud-installation)
 - :book: [Quick Start](#book-quick-start)
-  - :small_orange_diamond: [Embedding into Existing Projects](#small_orange_diamond-embedding-into-existing-projects)
-  - :small_orange_diamond: [Building from Scratch](#small_orange_diamond-building-from-scratch)
-  - :small_orange_diamond: [Visual Interface](#small_orange_diamond-visual-interface)
-  - :small_orange_diamond: [re-run](#small_orange_diamond-re-run)
-  - :small_orange_diamond: [backup](#small_orange_diamond-backup)
+    - :small_orange_diamond: [Embedding into Existing Projects](#small_orange_diamond-embedding-into-existing-projects)
+    - :small_orange_diamond: [Building from Scratch](#small_orange_diamond-building-from-scratch)
+    - :small_orange_diamond: [Visual Interface](#small_orange_diamond-visual-interface)
+    - :small_orange_diamond: [re-run](#small_orange_diamond-re-run)
+    - :small_orange_diamond: [backup](#small_orange_diamond-backup)
 - :scroll: [License](#scroll-license)
 
 # :cloud: Installation
@@ -199,6 +200,63 @@ issues = df.apply(
 
 ![backup_github](./images/backup_github.png)
 
+Full properties content:
+
+```
+{'agent': nan,
+ 'backup': {'23-03-17-003438': {'backend': 'github',
+                                'number': 9,
+                                'repo': '...'},
+            },
+ 'exception': nan,
+ 'execute': {'cwd': '~/Documents/Python/lumo',
+             'exec_argv': ['~/Documents/Python/lumo/a.py'],
+             'exec_bin': '~/.pyenv/versions/3.9.16/bin/python3.9',
+             'exec_file': '~/Documents/Python/lumo/a.py',
+             'repo': '~/Documents/Python/lumo'},
+ 'exp_name': 'my_exp_a',
+ 'git': {'commit': '1014b6b5',
+         'dep_hash': 'c93b8c4e340882f55cf0c8e125fa0203',
+         'repo': '~/Documents/Python/lumo'},
+ 'hooks': {'Diary': {'loaded': True, 'msg': ''},
+           'FinalReport': {'loaded': True, 'msg': ''},
+           'GitCommit': {'loaded': True, 'msg': ''},
+           'LastCmd': {'loaded': True, 'msg': ''},
+           'LockFile': {'loaded': True, 'msg': ''},
+           'RecordAbort': {'loaded': True, 'msg': ''}},
+ 'lock': {'accelerate': '0.16.0',
+          'decorator': '5.1.1',
+          'fire': '0.5.0',
+          'hydra': '1.3.2',
+          'joblib': '1.2.0',
+          'lumo': '0.15.0',
+          'numpy': '1.24.2',
+          'omegaconf': '2.3.0',
+          'psutil': '5.9.4',
+          'torch': '1.13.1'},
+ 'note': 'This is a Note',
+ 'params': {'alpha': 1, 'dataset': 'cifar10'},
+ 'paths': {'blob_root': '~/.lumo/blob',
+           'cache_root': '~/.lumo/cache',
+           'info_root': '~/.lumo/experiments'},
+ 'pinfo': {'hash': '0af4b77497c85bc5b65ccbdd9ff4ca0f',
+           'obj': {'argv': ['~/.pyenv/versions/3.9.16/bin/python3.9',
+                            '~/Documents/Python/lumo/a.py'],
+                   'pid': 63975,
+                   'pname': 'python3.9',
+                   'pstart': 1678898740.099484},
+           'pid': 63975},
+ 'progress': {'end': '23-03-16-004542',
+              'end_code': 0,
+              'last_edit_time': '23-03-16-004542',
+              'ratio': 1,
+              'start': '23-03-16-004542',
+              'update_from': None},
+ 'tags': [],
+ 'test_name': '230316.000.8ct',
+ 'trainer': nan}
+```
+
 # :scroll: License
 
 Distributed under the Apache License Version 2.0. See [LICENSE](./LICENSE) for more information.

From ae62888289e9ba3980f2f4773193f88606694824 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 14:11:40 +0800
Subject: [PATCH 92/95] =?UTF-8?q?Document=EF=BC=9A=20ignore=20test?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 pyproject.toml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pyproject.toml b/pyproject.toml
index e013350..189fab0 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -42,6 +42,7 @@ omit = [
     'src/lumo/vis/*',
     'src/lumo/decorators/*',
     'src/lumo/exp/agent.py',
+    'src/lumo/exp/lazy_panel.py',
     'src/lumo/analyse/*',
     'src/lumo/sketch/*',
     'src/lumo/core/record_backend/*',

From bd3ce965c637e5761013fe5fac9bf94dec9be0af Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 15:38:58 +0800
Subject: [PATCH 93/95] =?UTF-8?q?Document=EF=BC=9A=20update?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 README.ch.md | 9 ++++-----
 README.md    | 2 +-
 2 files changed, 5 insertions(+), 6 deletions(-)

diff --git a/README.ch.md b/README.ch.md
index abf21da..a9b4e24 100644
--- a/README.ch.md
+++ b/README.ch.md
@@ -79,7 +79,7 @@ exp.start()
 logger.add_log_dir(exp.mk_ipath())
 ```
 
-- 初始化参数
+- 初始化参数（代替 argparse 等）
 
 ```python
 # 替换基于 argparse 等的参数定义方法
@@ -90,7 +90,7 @@ params.from_args()  # python3 train.py --dataset=cifar100 --alpha=0.2
 print(params.to_dict())  # {"dataset": "cifar100", "alpha": 0.2}
 ```
 
-- 在训练过程中记录参数、存储信息
+- 在训练过程中记录参数、存储信息（代替手动管理路径、自己维护 AvgItem）
 
 ```python
 # 记录实验参数
@@ -204,7 +204,8 @@ issues = df.apply(
 
 ![backup_github](./images/backup_github.png)
 
-Full properties 内容:
+# Full properties
+
 ```
 {'agent': nan,
  'backup': {'23-03-17-003438': {'backend': 'github',
@@ -260,8 +261,6 @@ Full properties 内容:
  'trainer': nan}
 ```
 
-# More
-
 # :pencil: Acknowledge
 
 从 2020 年维护至今。感谢 lumo 陪我见证我的研究生生涯。
diff --git a/README.md b/README.md
index 7ac0c42..78ad25c 100644
--- a/README.md
+++ b/README.md
@@ -200,7 +200,7 @@ issues = df.apply(
 
 ![backup_github](./images/backup_github.png)
 
-Full properties content:
+# Full properties
 
 ```
 {'agent': nan,

From 380c1eab0e96b4d86ae4d9db85ca1f85302398a7 Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 15:39:15 +0800
Subject: [PATCH 94/95] example: update

---
 examples/imagenet.py | 53 +++++++++++++++++++++++++-------------------
 examples/moco.py     |  4 +++-
 2 files changed, 33 insertions(+), 24 deletions(-)

diff --git a/examples/imagenet.py b/examples/imagenet.py
index 31208f3..34fbf3a 100644
--- a/examples/imagenet.py
+++ b/examples/imagenet.py
@@ -6,7 +6,7 @@
 from PIL import Image
 from torch.utils.data import DataLoader
 import os
-
+import torch.multiprocessing as mp
 from torchvision.datasets.folder import default_loader
 
 from lumo import DatasetBuilder, MetricType, Trainer, TrainerParams, Meter, callbacks, DataModule
@@ -221,31 +221,38 @@ def test_step(self, batch, params: ParamsType = None) -> MetricType:
         return m
 
 
-def main():
+def main_worker(device, ngpus_per_node, args):
+    # create datamodule to contain dataloader
     params = LargeParams()
+    params.device = device
     params.from_args()
 
-    if params.multiprocessing_distributed and not is_dist():
-        command = ' '.join([
-            'accelerate', 'launch',
-            *sys.argv,
-        ])
-        run_command(command)
-    else:  # not distributed or in distribution environment
-        # create datamodule to contain dataloader
-        ds, test_ds = make_dataset(dummy=params.dummy)
-        dl = ds.DataLoader(batch_size=params.batch_size, num_workers=4)
-        test_dl = test_ds.DataLoader(batch_size=params.batch_size, num_workers=4)
-        dm = DataModule()
-        dm.regist_dataloader(train=dl, test=test_dl)
-
-        # with the input of params and dataloader, the initialization of models and optimizers in Trainer,
-        # then the output will be the trained parameters, metrics and logs.
-        trainer = LargeTrainer(params, dm=dm)
-
-        trainer.train()  # or trainer.train(dm=dl) if dm are not given above
-        trainer.test()  # or trainer.test(dm=dl)
-        trainer.save_last_model()
+    ds, test_ds = make_dataset(dummy=params.dummy)
+    dl = ds.DataLoader(batch_size=params.batch_size, num_workers=4)
+    test_dl = test_ds.DataLoader(batch_size=params.batch_size, num_workers=4)
+    dm = DataModule()
+    dm.regist_dataloader(train=dl, test=test_dl)
+
+    # with the input of params and dataloader, the initialization of models and optimizers in Trainer,
+    # then the output will be the trained parameters, metrics and logs.
+    trainer = LargeTrainer(params, dm=dm)
+
+    trainer.train()  # or trainer.train(dm=dl) if dm are not given above
+    trainer.test()  # or trainer.test(dm=dl)
+    trainer.save_last_model()
+
+
+def main():
+    # if params.multiprocessing_distributed and not is_dist():
+    #     mp.spawn(main, nprocs=torch.cuda.device_count(), args=(ngpus_per_node, args))
+    #     command = ' '.join([
+    #         'accelerate', 'launch',
+    #         *sys.argv,
+    #     ])
+    #     print(command)
+    #     run_command(command)
+    # else:  # not distributed or in distribution environment
+    pass
 
 
 if __name__ == '__main__':
diff --git a/examples/moco.py b/examples/moco.py
index 169aff9..14dff27 100644
--- a/examples/moco.py
+++ b/examples/moco.py
@@ -10,7 +10,7 @@
 
 from lumo import DatasetBuilder, MetricType, Trainer, TrainerParams, Meter, callbacks, DataModule
 from lumo.contrib import EMA, MemoryBank, StorageBank
-from lumo.contrib.accelerate.utils import send_to_device
+
 from lumo.contrib.nn.loss import contrastive_loss2
 from lumo.proc.path import cache_dir
 from torchvision.datasets.cifar import CIFAR10
@@ -19,6 +19,8 @@
 from torch import nn
 from torch.nn import functional as F
 
+from lumo.utils.device import send_to_device
+
 """define transforms"""
 
 

From 13eef3aa7371995a87253b67e286397277f65ffe Mon Sep 17 00:00:00 2001
From: sailist <sailist@outlook.com>
Date: Fri, 17 Mar 2023 15:46:28 +0800
Subject: [PATCH 95/95] Version: stable 1.0.0 version

---
 src/lumo/__init__.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/lumo/__init__.py b/src/lumo/__init__.py
index 5dd93f3..35697cc 100644
--- a/src/lumo/__init__.py
+++ b/src/lumo/__init__.py
@@ -1,7 +1,7 @@
 """
 
 """
-__version__ = "0.15.0"
+__version__ = "1.0.0"
 
 from .core import Params, ParamsType, MetricType, Meter, Record, TrainStage, BaseParams
 from .proc import glob