biondizzle/vllm
1
0
Fork 0
Code Issues Pull Requests Actions 2 Packages Projects Releases Wiki Activity

[Kernel] Delegate construction of FusedMoEQuantConfig to FusedMoEMethodBase subclasses (#22537)

Browse Source 
Signed-off-by: Bill Nell <bnell@redhat.com>
This commit is contained in:
bnellnm
2025-09-17 19:43:31 -04:00
committed by GitHub
parent e6585ddb45
commit 5963b98b46
68 changed files with 2698 additions and 2526 deletions
Download Patch File Download Diff File Expand all files Collapse all files

32
tests/kernels/moe/test_flashinfer.py
View File

@@ -6,6 +6,8 @@ import pytest
import torch
from vllm.config import ParallelConfig, VllmConfig, set_current_vllm_config
from vllm.model_executor.layers.fused_moe.config import (
fp8_w8a8_moe_quant_config)
from vllm.model_executor.layers.fused_moe.fused_moe import fused_experts
from vllm.model_executor.layers.fused_moe.layer import FusedMoE
from vllm.model_executor.layers.quantization.utils.flashinfer_utils import (
@@ -145,6 +147,14 @@ def test_flashinfer_per_tensor_moe_fp8_no_graph(
custom_routing_function=Llama4MoE.custom_routing_function,
scoring_func="softmax")
quant_config = fp8_w8a8_moe_quant_config(
w1_scale=td.w13_weight_scale,
w2_scale=td.w2_weight_scale,
a1_scale=td.a1_scale,
a2_scale=td.a2_scale,
per_act_token_quant=False,
)
output = fused_experts(
td.hidden_states,
td.w13_quantized,
@@ -153,15 +163,10 @@ def test_flashinfer_per_tensor_moe_fp8_no_graph(
topk_ids=topk_ids,
inplace=False,
activation="silu",
use_fp8_w8a8=True,
per_channel_quant=False,
global_num_experts=e,
expert_map=None,
w1_scale=td.w13_weight_scale,
w2_scale=td.w2_weight_scale,
a1_scale=td.a1_scale,
a2_scale=td.a2_scale,
apply_router_weight_on_input=True,
quant_config=quant_config,
)
flashinfer_output = apply_flashinfer_per_tensor_scale_fp8(
@@ -210,6 +215,14 @@ def test_flashinfer_cutlass_moe_fp8_no_graph(
custom_routing_function=Llama4MoE.custom_routing_function,
scoring_func="softmax")
quant_config = fp8_w8a8_moe_quant_config(
w1_scale=td.w13_weight_scale,
w2_scale=td.w2_weight_scale,
a1_scale=td.a1_scale,
a2_scale=td.a2_scale,
per_act_token_quant=False,
)
output = fused_experts(
td.hidden_states,
td.w13_quantized,
@@ -218,15 +231,10 @@ def test_flashinfer_cutlass_moe_fp8_no_graph(
topk_ids=topk_ids,
inplace=False,
activation="silu",
use_fp8_w8a8=True,
per_channel_quant=False,
global_num_experts=e,
expert_map=None,
w1_scale=td.w13_weight_scale,
w2_scale=td.w2_weight_scale,
a1_scale=td.a1_scale,
a2_scale=td.a2_scale,
apply_router_weight_on_input=True,
quant_config=quant_config,
)
td.layer.dp_size = 1