TensorFlow 2.2.0 未从 tensorflow.keras.models PyVer==3.8 导入 Sequential

Question

在尝试运行后出现的错误下方，如果回滚顶部的 Tensorflow 2.0 版本，该错误不会持续存在。 在 Jupyter Notebook 中自动完成时，所有部分都正常显示，只是无法加载。 是否有任何可能的解决方法来避免回滚到旧版本？

在：

from tensorflow.keras.models import Sequential

输出：

ImportError                               Traceback (most recent call last)
~\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py in <module>
     57 
---> 58   from tensorflow.python.pywrap_tensorflow_internal import *
     59 

~\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py in <module>
     27             return _mod
---> 28     _pywrap_tensorflow_internal = swig_import_helper()
     29     del swig_import_helper

~\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py in swig_import_helper()
     23             try:
---> 24                 _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
     25             finally:

~\Anaconda3\lib\imp.py in load_module(name, file, filename, details)
    241         else:
--> 242             return load_dynamic(name, filename, file)
    243     elif type_ == PKG_DIRECTORY:

~\Anaconda3\lib\imp.py in load_dynamic(name, path, file)
    341             name=name, loader=loader, origin=path)
--> 342         return _load(spec)
    343 

ImportError: DLL load failed: The specified module could not be found.

During handling of the above exception, another exception occurred:

ImportError                               Traceback (most recent call last)
<ipython-input-4-f05745da3b73> in <module>
----> 1 from tensorflow.keras.models import Sequential

~\Anaconda3\lib\site-packages\tensorflow\__init__.py in <module>
     39 import sys as _sys
     40 
---> 41 from tensorflow.python.tools import module_util as _module_util
     42 from tensorflow.python.util.lazy_loader import LazyLoader as _LazyLoader
     43 

~\Anaconda3\lib\site-packages\tensorflow\python\__init__.py in <module>
     48 import numpy as np
     49 
---> 50 from tensorflow.python import pywrap_tensorflow
     51 
     52 # Protocol buffers

~\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py in <module>
     67 for some common reasons and solutions.  Include the entire stack trace
     68 above this error message when asking for help.""" % traceback.format_exc()
---> 69   raise ImportError(msg)
     70 
     71 # pylint: enable=wildcard-import,g-import-not-at-top,unused-import,line-too-long

ImportError: Traceback (most recent call last):
  File "C:\Users\Michele\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 58, in <module>
    from tensorflow.python.pywrap_tensorflow_internal import *
  File "C:\Users\Michele\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 28, in <module>
    _pywrap_tensorflow_internal = swig_import_helper()
  File "C:\Users\Michele\Anaconda3\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 24, in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
  File "C:\Users\Michele\Anaconda3\lib\imp.py", line 242, in load_module
    return load_dynamic(name, filename, file)
  File "C:\Users\Michele\Anaconda3\lib\imp.py", line 342, in load_dynamic
    return _load(spec)
ImportError: DLL load failed: The specified module could not be found.


Failed to load the native TensorFlow runtime.

See https://www.tensorflow.org/install/errors

for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

Answer 1

简单使用：

from tensorflow.keras import Sequential

它会正常工作。
干杯

Answer 2

你可以在TensorFlow Keras中做这些顺序模型的例子。你也可以根据你的情况添加层。

from tensorflow import keras
from tensorflow.keras import layers
from tensorflow.keras import Sequential

model = Sequential()
# Adds a densely-connected layer with 64 units to the model:
model.add(layers.Dense(64, activation='relu'))
# Add another:
model.add(layers.Dense(64, activation='relu'))
# Add an output layer with 10 output units:
model.add(layers.Dense(10))

或

import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers

model = tf.keras.Sequential()
# Adds a densely-connected layer with 64 units to the model:
model.add(layers.Dense(64, activation='relu'))
# Add another:
model.add(layers.Dense(64, activation='relu'))
# Add an output layer with 10 output units:
model.add(layers.Dense(10))

Answer 3

截至最新的 TensorFlow 版本 >= 2.2.0，开发人员已修改（使其更容易）加载模型/层等的方式。

因此，Sequential 类不再在包tensorflow.keras.models 中，而是在tensorflow.keras 中