Comments (2)
fpjentzsch
commented on August 19, 2024
Hi, Conv1D is supported by combining a 1D variant of the ConvolutionInputGenerator (slidingwindow.h) and a normal MVAU (Matrix_Vector_Activate_Batch).
If you plan on using the FINN compiler: You can refer to this FINN-example to see the build-flow for a 1D CNN:
https://github.com/Xilinx/finn-examples/tree/main/build/vgg10-radioml
Most importantly, you will need to apply the Change3DTo4DTensors() transformation (https://github.com/Xilinx/finn-examples/blob/main/build/vgg10-radioml/custom_steps.py#L37) early on, since FINN works with 4D (NHWC) tensors internally, even for feature maps with only 1 spatial dimension.
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aspaul20
commented on August 19, 2024
Thanks for replying. I am not planning to use the compiler, I will use the library to implement the model.
Is this the variant you're referring to?
Also, other than the ConvolutionInputGenerator, what else would have to be changed in the standard convlayer?
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