shinh commented on PR #14536:
URL: https://github.com/apache/tvm/pull/14536#issuecomment-1539435547
Does this make sense to add this `qnn.softmax` implementation as an optional
feature? By default, we wouldn't enable qnn.softmax, but users could activate
it when they find its precision satisfactory for their use case. To be more
specific, I propose the following:
1. Add `@register_optional_fake_quantization_to_integer` and use it in
fake_quantization_to_integer.py for `softmax`:
```
@register_optional_fake_quantization_to_integer("nn.softmax")
def softmax(expr, type_map):
...
```
2. Modify `fake_quantization_to_integer.cc` so that optional rewriters will
be ignored unless users explicitly state they want to use quantized softmax by
something like
```
relay.transform.FakeQuantizationToInteger(optional_qnn_ops={"nn.softmax"})(mod)
```
I guess it's OK to relax checks of unittests if this feature is optional?
What are your thoughts?
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