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3 commits

Author SHA1 Message Date
Chen Fu
26b396418d
Block-wise 4b quantization matmul operator change (#18172)
### Description
Replace block-wise 4b quantization implementation


### Motivation and Context
In https://github.com/microsoft/onnxruntime/pull/18101 we have an
augmented block-wise 4b quantization interface and implementation. Here
we use this new implementation in onnxruntime contrib ops

---------

Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
2023-11-03 15:29:43 -07:00
Jambay Kinley
d30d4d372a
Add MatMul FP4 and NF4 Support (#18066)
### Description
Add a contrib op MatMulBnb4 (FP4 and NF4) and related toolchain to
support quantization on weight.

This PR adds:
- schema for contrib op MatMulBnb4 which can support FP4 (4-bit floating
point) and NF4 (4-bit NormalFloat) quantization on weight.
- a naive implementation for MatMulBnb4 on CPU and GPU, i.e.,
implemented like MatMul(A, Dequantize(B)).
- a special implementation for GemV for MatMulBnb4 and related benchmark
tool.
- tool to quantize model to FP4 or NF4.
2023-10-25 15:34:58 -07:00
Yufeng Li
11af34440a
Add MatMul 4bits support on GPU (#17890)
### Description
<!-- Describe your changes. -->
Add a contrib op MatMulNBits and related toolchain to support
quantization on weight. This PR only adds support for 4bits. It:

- add schema for contrib op MatMulNBits which can support 1-7 bits
quantization on weight.
- a naive implementation for 4bits MatMulNBits on CPU and GPU, i.e.,
implemented like MatMul(A, Dequantize(B)).
- a special implementation for GemV for 4bits MatMulNBits and related
benchmark tool
- tool to quantization model with 4bits. 

Next:
- add general and more efficient kernels for 4bits MatMulNBits on CPU
and GPU
2023-10-13 16:55:30 -07:00