[quant] Add support for quantization of Embedding{Bag} in dynamic quant APIs (#65674)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65674
Before this PR user had to use the eager mode static quantization APIs to quantize Embedding/EmbeddingBag modules.
With this PR they can use either the static or dynamic quantization APIs for Embedding quantization
The only qconfig supported for embedding quantization is float_qparams_weight_only_qconfig whcih is currently enforced in the from_float
method of the quantized Embedding/Embedding modules.
To combine embedding quantization with Linear dynamic quantization, user can use the qconfig_dict to specify different qconfig for each module type.
The prepare/convert APIs can still be used to quantize Embeddings, with the caveat that user need to ensure input to Embedding ops are FP32.
Addresses Issue #65185
ghstack-source-id: 139935419
Test Plan:
python test/test_quantization.py
Imported from OSS
Reviewed By: gchanan
Differential Revision: D31211199
fbshipit-source-id: 8c747881caee5ccbf8b93c6704b08d132049dea4
