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fix awq and dsv3 fused gemm compatible (#7735)

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AniZpZ
2025-07-03 13:56:57 +08:00
committed by GitHub
parent 8f844db699
commit 84f2e4a0f8
1 changed files with 15 additions and 2 deletions
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17
python/sglang/srt/models/deepseek_v2.py
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@@ -336,11 +336,17 @@ class DeepseekV2MoE(nn.Module):
else {}
),
)
is_packed_weight = (
self.shared_experts.gate_up_proj.quant_method.quant_config.get_name()
in ["awq", "moe_wna16"]
)
self.shared_experts_is_int8 = (
self.shared_experts.gate_up_proj.weight.dtype == torch.int8
not is_packed_weight
and self.shared_experts.gate_up_proj.weight.dtype == torch.int8
)
self.shared_experts_is_fp8 = (
self.shared_experts.gate_up_proj.weight.dtype == torch.float8_e4m3fn
not is_packed_weight
and self.shared_experts.gate_up_proj.weight.dtype == torch.float8_e4m3fn
)
if self.shared_experts_is_fp8:
assert (
@@ -894,8 +900,13 @@ class DeepseekV2AttentionMLA(nn.Module):
weight_names=["w_kc", "w_vc"], transpose_dims=[[1, 2], [1, 2]]
)
is_packed_weight = (
self.fused_qkv_a_proj_with_mqa.quant_method.quant_config.get_name()
in ["awq", "moe_wna16"]
)
self.use_min_latency_fused_a_gemm = (
hasattr(self, "fused_qkv_a_proj_with_mqa")
and not is_packed_weight
and self.fused_qkv_a_proj_with_mqa.weight.dtype == torch.bfloat16
and self.fused_qkv_a_proj_with_mqa.weight.shape[0] == 2112
and self.fused_qkv_a_proj_with_mqa.weight.shape[1] == 7168
@@ -905,10 +916,12 @@ class DeepseekV2AttentionMLA(nn.Module):
self.qkv_proj_with_rope_is_int8 = (
hasattr(self, "fused_qkv_a_proj_with_mqa")
and not is_packed_weight
and self.fused_qkv_a_proj_with_mqa.weight.dtype == torch.int8
)
self.qkv_proj_with_rope_is_fp8 = (
hasattr(self, "fused_qkv_a_proj_with_mqa")
and not is_packed_weight
and self.fused_qkv_a_proj_with_mqa.weight.dtype == torch.float8_e4m3fn
)