Towards supporting quantized structured kernels (#74560)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74560
This PR add support for quantized tensors with "unknown quantizer",
which means that we can use standard APIs like torch.empty to allocate
quantized tensors, with the understanding that we will set the
quantizer later. This makes meta functions applicable to quantized
tensors (they will allocate with unknown quantizer and the kernel
will set the quantizer later) and fixes a bug David Dang reported
where structured kernels give a weird error message when you call them
with quantized inputs.
This is not a complete support for quantized structured kernels because
I haven't actually tried porting any of the quantized implementations
to structured; qadd is probably a good choice to try first as it
does its broadcasting implementation using TensorIterator. My goal
here is just to show that the error message is better.
See also https://github.com/pytorch/pytorch/issues/52680
Signed-off-by: Edward Z. Yang <ezyangfb.com>
Test Plan: Imported from OSS
Reviewed By: mruberry
Differential Revision: D35317441
Pulled By: dzdang
fbshipit-source-id: ffb85b0e06ccbcc2b01052ca6760517684048b39
(cherry picked from commit 2a54b8b7bf15912240dc2f12d2cd71dc620001e1)
