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an error when running an optimizer #19
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Hi, |
Yes, I used scripts/convert_to_onnx.py for conversion to onnx. %628 : Float(1, 128, 32, 56) = onnx::Conv[dilations=[1, 1], group=1, kernel_shape=[1, 1], pads=[0, 0, 0, 0], strides=[1, 1]](%627, %Pose3D.prediction.feature_maps.0.0.weight, %Pose3D.prediction.feature_maps.0.0.bias) # /home/fc/anaconda3/envs/directron2/lib/python3.6/site-packages/torch/nn/modules/conv.py:342:0 |
So it looks like an internal error in MO. Try to use official model downloader and converter, model name is |
I will download the model and try it out. Thanks |
Same problem here. |
Thanks for the solution, @ZlodeiBaal! |
@ZlodeiBaal BTW, Anton, really love your posts on habr! 👑 |
@Daniil-Osokin |
Got an error when running optimizer below. Any idea why this happens:
python /opt/intel/openvino_2020.2.120/deployment_tools/model_optimizer/mo.py --input_model human-pose-estimation-3d.onnx --input=data --mean_values=data[128.0,128.0,128.0] --scale_values=data[255.0,255.0,255.0] --output=features,heatmaps,pafs
Model Optimizer arguments:
Common parameters:
- Path to the Input Model: /home/user/2TB/openvino/lightweight-human-pose-estimation-3d-demo.pytorch/human-pose-estimation-3d.onnx
- Path for generated IR: /home/user/2TB/openvino/lightweight-human-pose-estimation-3d-demo.pytorch/.
- IR output name: human-pose-estimation-3d
- Log level: ERROR
- Batch: Not specified, inherited from the model
- Input layers: data
- Output layers: features,heatmaps,pafs
- Input shapes: Not specified, inherited from the model
- Mean values: data[128.0,128.0,128.0]
- Scale values: data[255.0,255.0,255.0]
- Scale factor: Not specified
- Precision of IR: FP32
- Enable fusing: True
- Enable grouped convolutions fusing: True
- Move mean values to preprocess section: False
- Reverse input channels: False
ONNX specific parameters:
Model Optimizer version: 2020.2.0-60-g0bc66e26ff
[ ERROR ] Exception occurred during running replacer "REPLACEMENT_ID" (<class 'extensions.front.user_data_repack.UserDataRepack'>): No node with name features.
For more information please refer to Model Optimizer FAQ (https://docs.openvinotoolkit.org/latest/_docs_MO_DG_prepare_model_Model_Optimizer_FAQ.html), question #51.
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