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我在 Windows 10 机器上创建了一个 tensorflow 模型并使用以下方法保存它:
model.save('myfolder')
文件夹内
myfolder
我得到:
- saved_model.pb
- Variables folder
- Assets folder
现在我正在尝试在 Linux 机器中加载模型,所以我将文件夹路径作为模型路径传递来加载它:
model = tf.keras.models.load_model('myfolder')
它实际上检测了模型,但抛出了这个巨大的错误:
2020-09-27 18:43:57.980054: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:02.211495: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:02.376792: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:16.361762: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:18.184022: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:18.331177: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:19.087747: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:22.933245: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:23.074951: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:28.451176: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:28.597107: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:33.579605: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:33.742273: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:51.043732: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:44:57.151346: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
2020-09-27 18:45:00.168905: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:45:00.312153: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
2020-09-27 18:45:01.051383: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:45:01.190471: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
2020-09-27 18:45:01.395016: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:45:01.542457: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
2020-09-27 18:45:05.023475: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:45:05.235829: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
2020-09-27 18:45:05.568045: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
2020-09-27 18:45:06.300144: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:45:06.439828: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
2020-09-27 18:45:11.585829: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond/while' has 13 outputs but the _output_shapes attribute specifies shapes for 44 outputs. Output shapes may be inaccurate.
2020-09-27 18:45:11.729289: W tensorflow/core/graph/graph_constructor.cc:772] Node 'cond' has 5 outputs but the _output_shapes attribute specifies shapes for 45 outputs. Output shapes may be inaccurate.
Traceback (most recent call last):
File "main.py", line 95, in <module>
model = tf.keras.models.load_model('model')
File "/home/.local/lib/python3.7/site-packages/tensorflow_core/python/keras/saving/save.py", line 150, in load_model
return saved_model_load.load(filepath, compile)
File "/home/.local/lib/python3.7/site-packages/tensorflow_core/python/keras/saving/saved_model/load.py", line 89, in load
model = tf_load.load_internal(path, loader_cls=KerasObjectLoader)
File "/home/.local/lib/python3.7/site-packages/tensorflow_core/python/saved_model/load.py", line 541, in load_internal
export_dir)
File "/home/.local/lib/python3.7/site-packages/tensorflow_core/python/keras/saving/saved_model/load.py", line 118, in __init__
super(KerasObjectLoader, self).__init__(*args, **kwargs)
File "/home/.local/lib/python3.7/site-packages/tensorflow_core/python/saved_model/load.py", line 121, in __init__
self._load_all()
File "/home/.local/lib/python3.7/site-packages/tensorflow_core/python/saved_model/load.py", line 239, in _load_all
node, setter = self._recreate(proto)
File "/home/.local/lib/python3.7/site-packages/tensorflow_core/python/saved_model/load.py", line 322, in _recreate
return factory[kind]()
File "/home/.local/lib/python3.7/site-packages/tensorflow_core/python/saved_model/load.py", line 309, in <lambda>
"user_object": lambda: self._recreate_user_object(proto.user_object),
File "/home/.local/lib/python3.7/site-packages/tensorflow_core/python/saved_model/load.py", line 328, in _recreate_user_object
return self._recreate_base_user_object(proto)
File "/home/.local/lib/python3.7/site-packages/tensorflow_core/python/keras/saving/saved_model/load.py", line 216, in _recreate_base_user_object
return revived_cls._init_from_metadata(metadata) # pylint: disable=protected-access
File "/home/.local/lib/python3.7/site-packages/tensorflow_core/python/keras/saving/saved_model/load.py", line 297, in _init_from_metadata
revived_obj = cls(**init_args)
File "/home/.local/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/input_layer.py", line 86, in __init__
batch_size = batch_input_shape[0]
KeyError: 0
我已经从 GitHub 搜索了 Tensorflow 问题,但我还没有发现任何有趣的东西。我看到一个
SO answer建议使用加载的重量创建一个新模型,但我什至不能这样做,因为我在加载时遇到错误。
最佳答案
我刚刚解决了同样的问题。
检查用于训练和保存模型的 Tensorflow 版本以及用于加载模型的版本。它们必须相同,或者至少是 compatible versions .
关于python - 加载 .pb Tensorflow 模型时出错,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/64091029/
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