Error on running Super Resolution Model from ONNX

Question

Testing ONNX model for super resolution model, I have error running this sample program.

My ONNX version is 1.5.0 with onnxruntime 1.4.0. Onnxruntime was installed using pip. Pytorch version is 1.6.0

Error is at ort_session = onnxruntime.InferenceSession('/home/itc/pytorch/sub_pixel_cnn_2016/model/super-resolution-10.onnx')

The error is in loading onnx model.

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.
 

How can I solve the error?

Answer 1

super-resolution-10.onnx seems to load OK for me. I downloaded the file from https://github.com/onnx/models/blob/master/vision/super_resolution/sub_pixel_cnn_2016/model/super-resolution-10.onnx

$ pip install onnxruntime
...
Successfully installed onnxruntime-1.5.1

I also tried pip install onnxruntime==1.4.0 - also works fine.

Then tried to load it (there are bunch of warnings, but it loads ok):

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>

I think it's likely your ONNX file is corrupted, please try to load it with Netron to verify.

As a side note, PyTorch version and onnx version should be irrelevant for the loading.