@@ -468,7 +468,7 @@ def _update_states(self, scheduler_output: "SchedulerOutput") -> None:
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to_update .apply (pooling_params )
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backward_kwargs = {}
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- if vllm_version_is ("0.10.2 " ):
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+ if vllm_version_is ("0.10.2rc2 " ):
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backward_kwargs ["mm_kwargs" ] = new_req_data .mm_kwargs
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backward_kwargs ["mm_hashes" ] = new_req_data .mm_hashes
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backward_kwargs ["mm_positions" ] = new_req_data .mm_positions
@@ -490,7 +490,7 @@ def _update_states(self, scheduler_output: "SchedulerOutput") -> None:
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# Only relevant for models using M-RoPE (e.g, Qwen2-VL)
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if self .uses_mrope :
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- if vllm_version_is ("0.10.2 " ):
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+ if vllm_version_is ("0.10.2rc2 " ):
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self ._init_mrope_positions_0102 (self .requests [req_id ])
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else :
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self ._init_mrope_positions (self .requests [req_id ])
@@ -827,7 +827,7 @@ def _execute_mm_encoder(self, scheduler_output: "SchedulerOutput"):
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return
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# Batch the multi-modal inputs.
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- if vllm_version_is ("0.10.2 " ):
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+ if vllm_version_is ("0.10.2rc2 " ):
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mm_kwargs , mm_hashes_pos = self ._batch_mm_kwargs_from_scheduler_0102 (
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scheduler_output )
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else :
@@ -928,7 +928,7 @@ def _gather_mm_embeddings(
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) -> list [torch .Tensor ]:
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def _iter_mm_features (req_state : CachedRequestState ):
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- if vllm_version_is ("0.10.2 " ):
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+ if vllm_version_is ("0.10.2rc2 " ):
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# legacy path (to be removed later)
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assert req_state .mm_hashes is not None
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assert req_state .mm_positions is not None
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