[ao] Fix to InputWeightEqualization detector to handle Conv groups (#81971)
Summary: The current implementation of the InputWeightEqualization
detector broke when it was tested on MobileNetV2, and the reason for
this is that it wasn't able to properly handle groups in Conv layers,
and there also had to be some minor reshaping of the weights to handle
this as well.
In addition, the output was correspondingly tuned so that instead of
giving on output for each channel on each layer, it gives a single
suggestion per module and just lets it know how many of the channels
could benefit from input-weight equalization, and suggests it if it's
more than half.
There was also the realization that the test class didn't do a good job
of testing different dimensions for the batch vs. height vs. width, so
this was updated to be more comprehensive as well.
Test Plan: python test/test_quantization TestFxDetectInputWeightEqualization
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Pull Request resolved: https://github.com/pytorch/pytorch/pull/81971
Approved by: https://github.com/jerryzh168
