[oneDNN] Quantized MatMul with new API and features
Hi @penpornk Can you please review this PR ? Thank you!
_Reopened the closed PR https://github.com/tensorflow/tensorflow/pull/56792_

This PR introduces new API for quantized MatMul fusions. All fusions are implemented as single op _QuantizedMatMul with fused_ops attribute. This PR contains a number of features:

Weights can be quantized per-tensor or per-channel
MatMul + BiasAdd + Activation, where activation function can be any of {Relu, Relu6, LeakyRelu, Elu, Tanh, Sigmoid, GeluApproximate, GeluExact}
MatMul + BiasAdd + Add + Dequantize (when Add has same shape as the output of MatMul)
All fusions can have Dequantize as additional fusion.
All fusions can have Requantize as additional fusion, except the MatMul + BiasAdd + Add fusion.
When Dequantize is fused output can be float32
B matrix can be transposed.