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[Refactor] Remove Duplicate per_block_cast_to_fp8, Remove Dependencies of DeepGEMM (#21787)

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Signed-off-by: yewentao256 <zhyanwentao@126.com>
This commit is contained in:
Wentao Ye
2025-07-31 21:13:27 -04:00
committed by GitHub
parent 0bd409cf01
commit 3700642013
8 changed files with 55 additions and 132 deletions
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31
tests/kernels/moe/modular_kernel_tools/utils.py
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@@ -1,10 +1,10 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import math
import torch
import vllm._custom_ops as ops
from vllm.utils.deep_gemm import per_block_cast_to_fp8
def per_token_cast_to_fp8(
@@ -20,29 +20,6 @@ def per_token_cast_to_fp8(
return fp8_data.view(m, n + pad_size)[:, :n], (x_amax / 448.0).view(m, -1)
def per_block_cast_to_fp8(
x: torch.Tensor, block_size_k: int,
block_size_n: int) -> tuple[torch.Tensor, torch.Tensor]:
assert x.dim() == 2
m, n = x.shape
x_padded = torch.zeros(
(
int(math.ceil(m / block_size_k)) * block_size_k,
int(math.ceil(n / block_size_n)) * block_size_n,
),
dtype=x.dtype,
device=x.device,
)
x_padded[:m, :n] = x
x_view = x_padded.view(-1, block_size_k,
x_padded.size(1) // block_size_k, block_size_n)
x_amax = x_view.abs().float().amax(dim=(1, 3), keepdim=True).clamp(1e-4)
x_scaled = (x_view * (448.0 / x_amax)).to(torch.float8_e4m3fn)
x_scaled_sub = x_scaled.view_as(x_padded)[:m, :n].contiguous()
scales = (x_amax / 448.0).view(x_view.size(0), x_view.size(2))
return x_scaled_sub, scales
def make_non_quant_weights(
e: int,
n: int,
@@ -99,11 +76,9 @@ def make_block_quant_fp8_weights(
for i in range(e):
w1[i], w1_s[i] = per_block_cast_to_fp8(w1_bf16[i],
block_size_k=block_k,
block_size_n=block_n)
block_size=[block_k, block_n])
w2[i], w2_s[i] = per_block_cast_to_fp8(w2_bf16[i],
block_size_k=block_k,
block_size_n=block_n)
block_size=[block_k, block_n])
return w1, w2, w1_s, w2_s