将tensorflow导入为tf Tensorflow 2.0
我看到我可以像这样从tensorflow加载模型
image_model = tf.keras.applications.MobileNet(include_top=True, weights='imagenet', pooling='avg')
现在，我希望能够从本地计算机加载模型。我的问题是我找不到这样的预训练模型：
image_model = tf.keras.models.load_model('inception_v4.h5') (i used h5 from here https://github.com/titu1994/Inception-v4/releases?fbclid=IwAR0pK_CZaB9RwA92nvawNOha6DjY5xI0vtkc9Ff5HTATcFT9x5vGYBUXt5Q (first h5 model))
future: <Task finished coro=<server_task.<locals>.server_work() done,
defined at ....\x.py:249> exception=ValueError('No model found in config file.')>
Traceback (most recent call last):
File "....\x.py", line 280, in server_work
image_model, layers_indices = init(model_choice, layers_to_see)
File "....\x.py", line 146, in init
image_model = options[choice]()
#tf.keras.applications.MobileNetV2(include_top=True, weights='imagenet',
pooling='avg')
File "....\x.py", line 119, in model_H5_model
image_model = tf.keras.models.load_model('..../inception_v4.h5')
File "...\Python\Python37\lib\site-
packages\tensorflow_core\python\keras\saving\save.py", line 146, in
load_model
return hdf5_format.load_model_from_hdf5(filepath, custom_objects, compile)
File "...\AppData\Local\Programs\Python\Python37\lib\site-
packages\tensorflow_core\python\keras\saving\hdf5_format.py", line 165, in load_model_from_hdf5
raise ValueError('No model found in config file.')
ValueError: No model found in config file.
我也尝试过这样的模型
image_model = tf.keras.models.load_model('model.pb')
File "....\x.py", line 280, in server_work
image_model, layers_indices = init(model_choice, layers_to_see)
File "....\x.py", line 146, in init
image_model = options[choice]()
#tf.keras.applications.MobileNetV2(include_top=True, weights='imagenet',
pooling='avg')
File "....\x.py", line 119, in model_H5_model
image_model = tf.keras.models.load_model('.../model/inceptionv4.pb')
File "...\AppData\Local\Programs\Python\Python37\lib\site-
packages\tensorflow_core\python\keras\saving\save.py", line 149, in
load_model
loader_impl.parse_saved_model(filepath)
File "...\AppData\Local\Programs\Python\Python37\lib\site-
packages\tensorflow_core\python\saved_model\loader_impl.py", line 83, in
parse_saved_model
constants.SAVED_MODEL_FILENAME_PB))
OSError: SavedModel file does not exist at:
.../model/inceptionv4.pb/{saved_model.pbtxt|saved_model.pb}
我也尝试过的是这样的：
image_model = tf.keras.applications.MobileNet(include_top=True,
weights='imagenet', pooling='avg')
image_model.save('test') - > when trying to save i receive this error
File "\Python\Python37\lib\site-
packages\tensorflow_core\python\framework\func_graph.py", line 905, in
wrapper
raise e.ag_error_metadata.to_exception(e)
TypeError: in converted code:
relative to ...\Programs\Python\Python37\lib\site-packages:
tensorflow_core\python\eager\def_function.py:606 initialize_variables *
for v, init in initializer_map.items():
tensorflow_core\python\autograph\impl\api.py:438 converted_call
if not options.user_requested and
conversion.is_whitelisted_for_graph(f):
m = tf_inspect.getmodule(o)
tensorflow_core\python\util\tf_inspect.py:337 getmodule
return _inspect.getmodule(object)
pycallgraph\tracer.py:372 wrapper
if rest not in cache:
TypeError: unhashable type: 'ObjectIdentityDictionary'
tf.keras.models.load_model('test_model')
我想知道在哪里可以找到与tf.keras.models.load_model（）实际兼容的h5文件或pb（预训练模型）
基于第一个评论：
future: <Task finished coro=<server_task.<locals>.server_work() done, defined at c:\Users\...\Desktop\PrivateStuff\...\...\xx.py:249> exception=TypeError("in converted code:\n relative to C:\\Users\\...\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages:\n\n tensorflow_core\\python\\eager\\def_function.py:606 initialize_variables *\n for v, init in initializer_map.items():\n tensorflow_core\\python\\autograph\\impl\\api.py:438 converted_call\n if not options.user_requested and conversion.is_whitelisted_for_graph(f):\n tensorflow_core\\python\\autograph\\impl\\conversion.py:352 is_whitelisted_for_graph\n m = tf_inspect.getmodule(o)\n tensorflow_core\\python\\util\\tf_inspect.py:337 getmodule\n return _inspect.getmodule(object)\n pycallgraph\\tracer.py:372 wrapper\n if rest not in cache:\n\n TypeError: unhashable type: 'ObjectIdentityDictionary'\n")>
Traceback (most recent call last):
File "c:\Users\...\Desktop\PrivateStuff\...\...\xx.py", line 280, in server_work
image_model, layers_indices = init(model_choice, layers_to_see)
File "c:\Users\...\Desktop\PrivateStuff\...\...\xx.py", line 146, in init
image_model = options[choice]() #tf.keras.applications.MobileNetV2(include_top=True, weights='imagenet', pooling='avg')
File "c:\Users\...\Desktop\PrivateStuff\...\...\xx.py", line 55, in model_VGG16
image_model.save(r'c:\test')
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\keras\engine\network.py", line 975, in save
signatures, options)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\keras\saving\save.py", line 115, in save_model
signatures, options)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\keras\saving\saved_model\save.py", line 74, in save
save_lib.save(model, filepath, signatures, options)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\saved_model\save.py", line 870, in save
checkpoint_graph_view)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\saved_model\signature_serialization.py", line 64, in find_function_to_export
functions = saveable_view.list_functions(saveable_view.root)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\saved_model\save.py", line 141, in list_functions
self._serialization_cache)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\keras\engine\base_layer.py", line 2422, in _list_functions_for_serialization
.list_functions_for_serialization(serialization_cache))
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\keras\saving\saved_model\base_serialization.py", line 91, in list_functions_for_serialization
fns = self.functions_to_serialize(serialization_cache)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\keras\saving\saved_model\layer_serialization.py", line 79, in
functions_to_serialize
serialization_cache).functions_to_serialize)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\keras\saving\saved_model\layer_serialization.py", line 94, in
_get_serialized_attributes
serialization_cache)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\keras\saving\saved_model\model_serialization.py", line 47, in
_get_serialized_attributes_internal
default_signature = save_impl.default_save_signature(self.obj)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\keras\saving\saved_model\save_impl.py", line 206, in default_save_signature
fn.get_concrete_function()
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\eager\def_function.py", line 777, in get_concrete_function
self._initialize_uninitialized_variables(initializer_map)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\eager\def_function.py", line 616, in _initialize_uninitialized_variables
return initialize_variables.get_concrete_function()()
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\eager\function.py", line 1891, in get_concrete_function
graph_function, args, kwargs = self._maybe_define_function(args, kwargs)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\eager\function.py", line 2150, in _maybe_define_function
graph_function = self._create_graph_function(args, kwargs)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\eager\function.py", line 2041, in _create_graph_function
capture_by_value=self._capture_by_value),
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\framework\func_graph.py", line 915, in func_graph_from_py_func
func_outputs = python_func(*func_args, **func_kwargs)
File "C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow_core\python\framework\func_graph.py", line 905, in wrapper
raise e.ag_error_metadata.to_exception(e)
TypeError: in converted code:
relative to C:\Users\...\AppData\Local\Programs\Python\Python37\lib\site-packages:
tensorflow_core\python\eager\def_function.py:606 initialize_variables *
for v, init in initializer_map.items():
tensorflow_core\python\autograph\impl\api.py:438 converted_call
if not options.user_requested and conversion.is_whitelisted_for_graph(f):
tensorflow_core\python\autograph\impl\conversion.py:352 is_whitelisted_for_graph
m = tf_inspect.getmodule(o)
tensorflow_core\python\util\tf_inspect.py:337 getmodule
return _inspect.getmodule(object)
pycallgraph\tracer.py:372 wrapper
if rest not in cache:
TypeError: unhashable type: 'ObjectIdentityDictionary'
答案 0 :(得分：1)
我复制了您的代码以加载MobileNet。如果您提供保存模型的完整路径，则此方法有效。请参见下面的代码。请注意，当您使用weight ='imagenet'加载模型时，将为在imagenet数据集上训练的模型设置权重。您无需加载任何砝码。现在，如果要为在其他数据集上预先训练的模型加载权重，请首先实例化该模型，如下所示。然后使用model.load_weights加载特定的权重。
image_model = tf.keras.applications.MobileNet(include_top=True,
weights='imagenet', pooling='avg')
image_model.save(r'c:\test')