deepreplay 包出现问题：ValueError：无法创建组（名称已存在）

Question

最近我在使用deepreplay 包时遇到了一个问题，因为它的 Traceback 如下：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-43-c3b5d8180301> in <module>()
----> 1 model.fit(X, y, epochs=50, batch_size=16, callbacks=[replay])

2 frames
/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py in error_handler(*args, **kwargs)
     65     except Exception as e:  # pylint: disable=broad-except
     66       filtered_tb = _process_traceback_frames(e.__traceback__)
---> 67       raise e.with_traceback(filtered_tb) from None
     68     finally:
     69       del filtered_tb

/usr/local/lib/python3.7/dist-packages/deepreplay/callbacks.py in on_train_begin(self, logs)
     83         self.n_epochs = self.params['epochs']
     84 
---> 85         self.group = self.handler.create_group(self.group_name)
     86         self.group.attrs['samples'] = self.params['samples']
     87         self.group.attrs['batch_size'] = self.params['batch_size']

/usr/local/lib/python3.7/dist-packages/h5py/_hl/group.py in create_group(self, name, track_order)
     63             name, lcpl = self._e(name, lcpl=True)
     64             gcpl = Group._gcpl_crt_order if track_order else None
---> 65             gid = h5g.create(self.id, name, lcpl=lcpl, gcpl=gcpl)
     66             return Group(gid)
     67 

h5py/_objects.pyx in h5py._objects.with_phil.wrapper()

h5py/_objects.pyx in h5py._objects.with_phil.wrapper()

h5py/h5g.pyx in h5py.h5g.create()

ValueError: Unable to create group (name already exists)

我分享了2019 年 8 月 2 日可以运行的google colab笔记本，但现在它抛出了这个KeyError: 'samples' 请检查笔记本并随意运行它以进行快速调试。

以下是google colab中的配置和包版本：

matplotlib==3.2.2
matplotlib-inline==0.1.3
matplotlib-venn==0.11.6
numpy==1.19.5
pandas==1.1.5
pandas-datareader==0.9.0
pandas-gbq==0.13.3
pandas-profiling==1.4.1
scikit-learn==1.0.1
scipy==1.4.1
seaborn==0.11.2
sklearn-pandas==1.8.0
Python 3.7.12

这是完整的代码：

matplotlib==3.2.2
matplotlib-inline==0.1.3
matplotlib-venn==0.11.6
numpy==1.19.5
pandas==1.1.5
pandas-datareader==0.9.0
pandas-gbq==0.13.3
pandas-profiling==1.4.1
scikit-learn==1.0.1
scipy==1.4.1
seaborn==0.11.2
sklearn-pandas==1.8.0
Python 3.7.12

我在这里和这里发现了与通过 hdf5 文件保存模型相关的类似未解决问题。我尝试根据一些建议12195#和此处保存模型，tf 而不是h5在replay_filename其中保存不成功。SoF里有很多这方面的帖子

在Github 问题之后，我尝试并替换了以下脚本，以便在运行单元时动态更改名称：

#!pip install deepreplay
from keras.models import Sequential
from keras.layers import Dense
#from keras.optimizers import SGD
from tensorflow.keras.optimizers import SGD
from keras.initializers import glorot_normal, normal

model = Sequential()
model.add(Dense(input_dim=2,
                units=2,
                activation='sigmoid',
                kernel_initializer=glorot_normal(seed=42),
                name='hidden'))
model.add(Dense(units=1,
                activation='sigmoid',
                kernel_initializer=normal(seed=42),
                name='output'))

model.compile(loss='binary_crossentropy', optimizer=SGD(learning_rate=0.05), metrics=['acc'])

from deepreplay.callbacks import ReplayData
from deepreplay.datasets.parabola import load_data
from deepreplay.replay import Replay

X, y = load_data()

replay = ReplayData(X, y, filename='hyperparms_in_action.h5', group_name='part1')
model.fit(X, y, epochs=50, batch_size=16, callbacks=[replay])

但是，问题中提到的那些错误仍然存​​在，并且当我最近在 Google colab 笔记本中运行它们时无法找出问题所在。此外，我检查了这篇文章，如果问题是“覆盖文件中包含的给定组内的数据h5”。

我还尝试逐行调试，如果您检查笔记本，我会收到以下错误：

import datetime as dt
dtime = dt.time()
now = dt.datetime.now()
zeit = now.strftime("%Y-%m-%d %H:%M:%S")
print(f"Last update of notebook:{zeit}")

X, y = load_data()

#replay = ReplayData(X, y, filename='hyperparms_in_action.h5', group_name='part1')
replay = ReplayData(X, y, filename='hyperparms_in_action{{zeit}.h5', group_name=f'part1_{zeit}')

任何帮助将不胜感激。