我的 ONNX 版本是 1.5.0，onnxruntime 1.4.0。 Onnxruntime 是使用 pip 安装的。 Pytorch 版本是 1.6.0
错误位于
ort_session = onnxruntime.InferenceSession('/home/itc/pytorch/sub_pixel_cnn_2016/model/super-resolution-10.onnx')错误在于加载onnx模型。
Traceback (most recent call last):
File "test.py", line 73, in <module>
ort_session = onnxruntime.InferenceSession('/home/itc/pytorch/sub_pixel_cnn_2016/model/super-resolution-10.onnx')
File "/home/itc/pytorch/lib/python3.7/site-packages/onnxruntime/capi/session.py", line 158, in __init__
self._load_model(providers or [])
File "/home/itc/pytorch/lib/python3.7/site-packages/onnxruntime/capi/session.py", line 166, in _load_model
True)
RuntimeError: /onnxruntime_src/onnxruntime/core/session/inference_session.cc:238 onnxruntime::InferenceSession::InferenceSession(const onnxruntime::SessionOptions&, const onnxruntime::Environment&, const string&) status.IsOK() was false. Given model could not be parsed while creating inference session. Error message: Protobuf parsing failed.
如何解决该错误？
super-resolution-10.onnx$ pip install onnxruntime
...
Successfully installed onnxruntime-1.5.1
我也尝试过
pip install onnxruntime==1.4.0然后尝试加载它（有一堆警告，但加载正常）：
In [1]: import onnxruntime
In [2]: onnxruntime.InferenceSession("super-resolution-10.onnx")
2020-10-12 23:25:23.486256465 [W:onnxruntime:, graph.cc:1030 Graph] Initializer conv1.bias appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2020-10-12 23:25:23.486293664 [W:onnxruntime:, graph.cc:1030 Graph] Initializer conv1.weight appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2020-10-12 23:25:23.486308563 [W:onnxruntime:, graph.cc:1030 Graph] Initializer conv2.bias appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2020-10-12 23:25:23.486322663 [W:onnxruntime:, graph.cc:1030 Graph] Initializer conv2.weight appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2020-10-12 23:25:23.486335363 [W:onnxruntime:, graph.cc:1030 Graph] Initializer conv3.bias appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2020-10-12 23:25:23.486348462 [W:onnxruntime:, graph.cc:1030 Graph] Initializer conv3.weight appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2020-10-12 23:25:23.486361862 [W:onnxruntime:, graph.cc:1030 Graph] Initializer conv4.bias appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
2020-10-12 23:25:23.486384161 [W:onnxruntime:, graph.cc:1030 Graph] Initializer conv4.weight appears in graph inputs and will not be treated as constant value/weight. This may prevent some of the graph optimizations, like const folding. Move it out of graph inputs if there is no need to override it, by either re-generating the model with latest exporter/converter or with the tool onnxruntime/tools/python/remove_initializer_from_input.py.
Out[2]: <onnxruntime.capi.session.InferenceSession at 0x7f58367236d0>
我认为您的ONNX文件可能已损坏，请尝试使用Netron加载它来验证。
顺便说一句，PyTorch 版本和 onnx 版本应该与加载无关。
在我的例子中，我将模型路径作为参数从命令行传递给 Python 脚本。该脚本需要模型文件的路径，而我将路径传递给包含模型的目录，这导致了相同的错误......所以这个愚蠢的错误也可能导致相同的“神秘”错误。