Update qkeras converter for array and auto po2 scale#135
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jurevreca12 wants to merge 13 commits intofastmachinelearning:mainfrom
Open
Update qkeras converter for array and auto po2 scale#135jurevreca12 wants to merge 13 commits intofastmachinelearning:mainfrom
jurevreca12 wants to merge 13 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.
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This PR updates the QKeras converter to enable it to convert neural networks with tensor scale factors, and with scale factors set to "auto_po2".
Previously the converter added a "Quant" node for every "quantized_bits" function in qkeras. Now it adds an additional "Mul" node after a Quant node. This is because of differences in how QKeras and QONNX handle dequantization.
This additional "Mul" node might be a problem for downstream onnx uses, but can be removed when scale factors are equal to one using a transform.
This PR "follows" after PR: Rounding mode new #134 which introduces additional rounding modes. This is why it contains rounding mode changes for now (since they are not yet merged into main).