Add proper support for Binarized and binary neural nets in the QKeras converter#141
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jurevreca12 wants to merge 29 commits intofastmachinelearning:mainfrom
Open
Add proper support for Binarized and binary neural nets in the QKeras converter#141jurevreca12 wants to merge 29 commits intofastmachinelearning:mainfrom
jurevreca12 wants to merge 29 commits intofastmachinelearning:mainfrom
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…rn new rounding modes.
Fixed rounding_mode specifier in convert_quantized_bits
Commented out assertion on non-representability
…ay_and_auto_po2_scale Merging changes from rounding_mode_new.
…nto HEAD Merge changes from the new converter
…ization_qkeras_converter
…ed up by the normal converter flow. Added an extra InferShape transform
Added a pure binarized networka s a test for qkeras converter
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This PR cleans up some of the QKeras2QONNX converter code and inserts BinaryQuant nodes instead of Quant nodes for
qkeras.binaryinstances. This PR should follow PR: #139.As this changes the nodes created by the converter it could affect downstream users.
Questions:
channel_order_rewriters._to_channel_first_handler(ctx, quant_act_node). I removed this and the tests still passed, however I am not sure what that was doing there. Does anyone know?# BUG: 1-bit Quant ops currently not exported correctly, manually convert to bipolar valuesSo, should this PR request delete this workaround? or does anyone still depend on this?