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[MoE][Refactor] Remove most arguments to FusedMoEMethodBase.apply (#29066)

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Signed-off-by: Bill Nell <bnell@redhat.com>
Signed-off-by: Tyler Michael Smith <tlrmchlsmth@gmail.com>
Co-authored-by: Robert Shaw <114415538+robertgshaw2-redhat@users.noreply.github.com>
Co-authored-by: Lucas Wilkinson <LucasWilkinson@users.noreply.github.com>
Co-authored-by: Tyler Michael Smith <tlrmchlsmth@gmail.com>
This commit is contained in:
bnellnm
2025-12-09 16:48:25 -05:00
committed by GitHub
parent 7618dc973d
commit 00e5cbb967
18 changed files with 318 additions and 872 deletions
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26
vllm/model_executor/layers/quantization/gptq_marlin.py
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@@ -1,7 +1,6 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from collections.abc import Callable
from copy import deepcopy
from typing import Any, Optional
@@ -790,25 +789,8 @@ class GPTQMarlinMoEMethod(FusedMoEMethodBase):
layer: FusedMoE,
x: torch.Tensor,
router_logits: torch.Tensor,
top_k: int,
renormalize: bool,
use_grouped_topk: bool = False,
topk_group: int | None = None,
num_expert_group: int | None = None,
global_num_experts: int = -1,
expert_map: torch.Tensor | None = None,
custom_routing_function: Callable | None = None,
scoring_func: str = "softmax",
routed_scaling_factor: float = 1.0,
e_score_correction_bias: torch.Tensor | None = None,
apply_router_weight_on_input: bool = False,
activation: str = "silu",
enable_eplb: bool = False,
expert_load_view: torch.Tensor | None = None,
logical_to_physical_map: torch.Tensor | None = None,
logical_replica_count: torch.Tensor | None = None,
) -> torch.Tensor | tuple[torch.Tensor, torch.Tensor]:
assert activation == "silu", "Only SiLU activation is supported."
assert layer.activation == "silu", "Only SiLU activation is supported."
topk_weights, topk_ids, _ = layer.select_experts(
hidden_states=x,
@@ -829,9 +811,9 @@ class GPTQMarlinMoEMethod(FusedMoEMethodBase):
input_global_scale1=getattr(layer, "w13_input_global_scale", None),
input_global_scale2=getattr(layer, "w2_input_global_scale", None),
quant_type_id=self.quant_type.id,
apply_router_weight_on_input=apply_router_weight_on_input,
global_num_experts=global_num_experts,
expert_map=expert_map,
apply_router_weight_on_input=layer.apply_router_weight_on_input,
global_num_experts=layer.global_num_experts,
expert_map=layer.expert_map,
g_idx1=layer.w13_g_idx,
g_idx2=layer.w2_g_idx,
sort_indices1=layer.w13_g_idx_sort_indices,