andrewor14 b6e85eb8d5 [quant][pt2] Support quantized conv bias in QAT fusion (#112528) ... Summary: Previously QAT fusion assumes bias is not quantized. This works for the existing XNNPACKQuantizer, but not for custom quantizers that wish to quantize the bias. This commit supports this by adding the necessary patterns. This requires refactoring the code, however, since it previously assumed that there will only be one pair of q-dq (from conv weight) in the matched pattern, and this is no longer true. Test Plan: python test/test_quantization.py TestQuantizePT2EQAT.test_qat_conv_bn_bias_derived_qspec Reviewers: jerryzh168, kimishpatel Subscribers: jerryzh168, kimishpatel, supriyar Differential Revision: [D50856377](https://our.internmc.facebook.com/intern/diff/D50856377) Pull Request resolved: https://github.com/pytorch/pytorch/pull/112528 Approved by: https://github.com/jerryzh168		2023-11-06 17:58:57 +00:00
..
ao_migration	ao migration: remove package test as this behavior is tested by other things (#94422)	2023-02-13 16:33:40 +00:00
bc	[BE] Enable ruff's UP rules and autoformat test/ (#105434)	2023-07-19 20:36:06 +00:00
core	[Quant] [PT2] Enable Decomposed quant per tensor/channel to accept bfloat16 input (#112225)	2023-11-03 23:47:43 +00:00
eager	[pytorch][ao] Add torch.matmul in FloatFunctional/QFunctional (#106831)	2023-08-10 22:43:36 +00:00
fx	Back out "Enable pickling model prepared with QAT qconfig" (#110392)	2023-10-05 14:41:00 +00:00
jit	Revert "Remove deprecated fbgemm operators (#104535)"	2023-10-25 16:34:16 +00:00
pt2e	[quant][pt2] Support quantized conv bias in QAT fusion (#112528)	2023-11-06 17:58:57 +00:00
serialized	[ao] fix incorrect integer cast on histogram observer bounds (#90355)	2022-12-12 20:30:44 +00:00
__init__.py