62 lines
1.3 KiB
Python
62 lines
1.3 KiB
Python
import torch
|
|
|
|
def gptq_marlin_gemm(
|
|
a: torch.Tensor,
|
|
b_q_weight: torch.Tensor,
|
|
b_scales: torch.Tensor,
|
|
g_idx: torch.Tensor,
|
|
perm: torch.Tensor,
|
|
workspace: torch.Tensor,
|
|
num_bits: int,
|
|
size_m: int,
|
|
size_n: int,
|
|
size_k: int,
|
|
is_k_full: bool,
|
|
) -> torch.Tensor:
|
|
"""
|
|
Matrix multiplication using Marlin kernels. This is an extension of
|
|
`marlin_gemm` that supports converted GPTQ kernels.
|
|
"""
|
|
...
|
|
|
|
def gptq_marlin_24_gemm(
|
|
a: torch.Tensor,
|
|
b_q_weight: torch.Tensor,
|
|
b_meta: torch.Tensor,
|
|
b_scales: torch.Tensor,
|
|
workspace: torch.Tensor,
|
|
num_bits: int,
|
|
size_m: int,
|
|
size_n: int,
|
|
size_k: int,
|
|
) -> torch.Tensor:
|
|
"""
|
|
Matrix multiplication using Marlin kernels. This is an extension of
|
|
`marlin_gemm` that supports 2:4 sparsity.
|
|
"""
|
|
...
|
|
|
|
def gptq_marlin_repack(
|
|
b_q_weight: torch.Tensor,
|
|
perm: torch.Tensor,
|
|
size_k: int,
|
|
size_n: int,
|
|
num_bits: int,
|
|
) -> torch.Tensor:
|
|
"""Repack GPTQ parameters for Marlin kernels."""
|
|
...
|
|
|
|
def marlin_gemm(
|
|
a: torch.Tensor,
|
|
b_q_weight: torch.Tensor,
|
|
b_scales: torch.Tensor,
|
|
workspace: torch.Tensor,
|
|
size_m: int,
|
|
size_n: int,
|
|
size_k: int,
|
|
) -> torch.Tensor:
|
|
"""
|
|
Matrix multiplication using Marlin kernels.
|
|
"""
|
|
...
|