[quant][fx] Make scale, zero_point buffers in the model and use FQN (for quantized ops) (#51166)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/51166
Currently scale and zero_point values are stored as constant values in the graph.
This prevents these values from being updated in the graph and also does not enable saving
these values to state_dict
After this PR we store scale/zero_point values for quantized ops as buffers in the root module
and createe get_attr nodes for them in the graph.
We also use the FQN of the module where the quantized ops are present to name these attributes so
that they can be uniquely identified and mapped to quantized ops.
Test Plan:
python test/test_quantization.py TestQuantizeFx.test_qparams_buffers
Imported from OSS
Reviewed By: jerryzh168
Differential Revision: D26092965
fbshipit-source-id: b549b2d3dccb45c5d38415ce95a09c26f5bd590b
