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Error loading MixNet model

RicardBorras
Beginner
1,993 Views

Hello,

when loading a MixNet model converted from ONNX using model converter, I get an error saying "Convolution initialization. Group splitted mode are used together with direct group specification" when model is loaded. Error is reproduced in 2020.3 and 2020.4 releases in Ubuntu Linux 18.04

ONNX model is converted from a pretrained Pytorch model from https://github.com/rwightman/gen-efficientnet-pytorch.

and converted using:

python mo_onnx.py --input_model=<ONNX_FILE> --output_dir=<OUTPUT_FOLDER>

Find attached ONNX file and converted models

Any help?

Thanks,

Ricard

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Munesh_Intel
Moderator
1,949 Views

Hi Ricard,


I’ve validated your MixNet model, and am seeing the same errors as well. This is due to MixNet not being supported officially by OpenVINO.

Details about supported PyTorch models are available at the following page:

https://docs.openvinotoolkit.org/2020.4/openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_ONNX.html#supported_pytorch_models_via_onnx_conversion


Regards,

Munesh


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Munesh_Intel
Moderator
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Hi Ricard,

EfficientNet B0, EfficientNet B5 and EfficientNet B7 are available as public models in Open Model Zoo. For your case, I’ve validated EfficientNet B0 using OpenVINO 2020.4 in Ubuntu 18.04 LTS, and the model is working fine with Image Classification Python Sample.


I suggest you try the following:


I converted the PyTorch model to ONNX using the following command available from https://github.com/rwightman/gen-efficientnet-pytorch


python3 onnx_export.py --model efficientnet_b0 ./efficientnet-b0.onnx


The Model Optimizer command that I used is as follows:


python3 /opt/intel/openvino/deployment_tools/model_optimizer/mo_onnx.py --input_model /home/username/Desktop/efficientnet-b0.onnx --reverse_input_channels --input_shape [1,3,224,224]


The Model Optimizer conversion parameters for efficientnet-b0-pytorch is available at

https://github.com/openvinotoolkit/open_model_zoo/blob/master/models/public/efficientnet-b0-pytorch/model.yml#L64


Similarly, Model Optimizer conversion parameters for efficientnet-b5-pytorch and efficientnet-b7-pytorch are available at

https://github.com/openvinotoolkit/open_model_zoo/blob/master/models/public/efficientnet-b5-pytorch/model.yml#L70


https://github.com/openvinotoolkit/open_model_zoo/blob/master/models/public/efficientnet-b7-pytorch/model.yml#L69


Regards,

Munesh




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RicardBorras
Beginner
1,966 Views

Hi,

I haven't tryied EfficientNET models from this repo, I am trying to use MIXNET models (following same steps that you supplied for EfficientNET). Can you verify if your approach works for Mixnet models?

thanks,

Ricard 

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Munesh_Intel
Moderator
1,950 Views

Hi Ricard,


I’ve validated your MixNet model, and am seeing the same errors as well. This is due to MixNet not being supported officially by OpenVINO.

Details about supported PyTorch models are available at the following page:

https://docs.openvinotoolkit.org/2020.4/openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_ONNX.html#supported_pytorch_models_via_onnx_conversion


Regards,

Munesh


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Munesh_Intel
Moderator
1,913 Views

Hi Ricard,

This thread will no longer be monitored since we have provided a solution. If you need any additional information from Intel, please submit a new question.


Regards,

Munesh


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