[Misc] Remove no-op self-assignments across vLLM (#55988)
Signed-off-by: shaolila <shaolila@buaa.edu.cn> Co-authored-by: shaolila <shaolila@buaa.edu.cn>
Adababy committed
Sep 16, 2026 at 17:17 UTC
ceb87de065b9cbdaffd34a0e6aed86c99e772b95
4 files changed
+9
-12
vllm/model_executor/layers/fused_moe/routed_experts.py
+8
-7
@@ -615,14 +615,15 @@ class RoutedExperts(PluggableLayer):
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# compressed-tensors checkpoints with packed weights are stored flipped
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# TODO (mgoin): check self.quant_method.quant_config.quant_format
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# against known CompressionFormat enum values that have this quality
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- if quant_method_name in (
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- "CompressedTensorsWNA16MoEMethod",
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- "CompressedTensorsW4A16FlydslMoEMethod",
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+ if (
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+ quant_method_name
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+ in (
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+ "CompressedTensorsWNA16MoEMethod",
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+ "CompressedTensorsW4A16FlydslMoEMethod",
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+ )
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+ and is_transposed
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):
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- if is_transposed:
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- loaded_weight = loaded_weight.t().contiguous()
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- else:
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- loaded_weight = loaded_weight
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+ loaded_weight = loaded_weight.t().contiguous()
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if shard_id not in ("w1", "w2", "w3"):
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raise ValueError(f"shard_id must be ['w1','w2','w3'] but got {shard_id}.")
vllm/model_executor/models/deepencoder.py
+1
-3
@@ -780,9 +780,7 @@ class DeepCLIPVisionEmbeddings(CLIPVisionEmbeddings):
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self, pixel_values: torch.Tensor, patch_embeds: torch.Tensor | None = None
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) -> torch.Tensor:
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batch_size = pixel_values.shape[0]
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- if patch_embeds is not None:
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- patch_embeds = patch_embeds
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- else:
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+ if patch_embeds is None:
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patch_embeds = self.patch_embedding(pixel_values)
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patch_embeds = patch_embeds.flatten(2).transpose(1, 2)
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vllm/model_executor/models/mimo_v2_omni.py
-1
@@ -964,7 +964,6 @@ class MiMoV2OmniMultiModalProcessor(BaseMultiModalProcessor[MiMoV2OmniProcessing
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assert isinstance(va_item, (list, tuple)) and len(va_item) == 2
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vid, audio_src = va_item
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va_item = VideoAudioInput(video=vid, audio=audio_src)
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- vid = vid
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# Convert video frames to (TCHW, timestamps) if needed
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if (
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isinstance(vid, tuple)
vllm/model_executor/models/step3p5.py
-1
@@ -173,7 +173,6 @@ class Step3p5Attention(nn.Module):
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rope_scaling = None
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if sliding_window is not None and enable_sliding_window:
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- sliding_window = sliding_window
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if swa_num_attention_heads is not None:
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num_heads = swa_num_attention_heads
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self.total_num_heads = swa_num_attention_heads