unsupported layers #648
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The onnx front end is undergoing quite a few revisions, with the new version in the ingest-qonnx-master branch. The new version depends on some preprocessing, however, from the https://github.com/fastmachinelearning/qonnx toolkit, in particular, one needs to do some cleaning (https://github.com/fastmachinelearning/qonnx/blob/main/src/qonnx/util/cleanup.py) and convert to channels last (https://github.com/fastmachinelearning/qonnx/blob/main/src/qonnx/util/to_channels_last.py). Those exist as standalone executibles when you install qunnox, too. One thing I noticed is that your network has a Gemm. That's not supported in the new parsing, and one should use the https://github.com/fastmachinelearning/qonnx/blob/main/src/qonnx/transformation/gemm_to_matmul.py transfromation to convert it to MatMul and Add. Currently I believe that only works if your nodes are single precision, not double precision. (We will make it more universal in the future.) |
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I have tried to make change the channels to last but i get this error |
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I have a simple model with conv1D with pad ,adaptiveavgpool1d and a squeeze function , when i tried to convert the model form onnx to hls using hls4ml.converter_onnx_to_hls , it gave me unsupported layer 'pad' error , i remove the padding layer then it gave me unsupported layer 'squeeze' then I tried using skip layer by adding squeeze to skip layer list and again i encounter the following error


My question is , do we have pad and squeeze function in hls4ml . If yes then why i am getting the error of not supported layers and when i go through the onnx_to_hls.py i can see the pad function implemented there.
Any help will be much appertained
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