[quant][core] Add quantize/dequantize ops for decomposed quantized Tensor representation (#87093)
Summary:
Added q/dq implementation for out of core (decomposed) quantized Tensor representation, meaning that
instead of storing quantization parameters (e.g. scale/zero_point) in a separate quantized Tensor object, we will store
quantization parameters in the argument of operators.
```
quantize(float32_tensor, scale, zero_point, dtype) -> int8_tensor
dequantize(int8_tensor, scale, zero_point, dtype) -> float32_tensor
```
Test Plan:
python test/test_quantization.py TestQuantizedTensor.test_decomposed_quantize
python test/test_quantization.py TestQuantizedTensor.test_decomposed_dequantize
Reviewers:
Subscribers:
Tasks:
Tags:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/87093
Approved by: https://github.com/dzdang, https://github.com/z-a-f
