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Remove global CUDA graph pool
Signed-off-by: Woosuk Kwon <woosuk@thinkingmachines.ai>
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@ -82,7 +82,7 @@ class CUDAGraphWrapper:
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# TODO: in the future, if we want to use multiple
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# streams, it might not be safe to share a global pool.
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# only investigate this when we use multiple streams
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self.graph_pool = current_platform.get_global_graph_pool()
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self.graph_pool = current_platform.graph_pool_handle()
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if cudagraph_options is None:
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cudagraph_options = CUDAGraphOptions()
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@ -140,8 +140,6 @@ class Platform:
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additional_env_vars: list[str] = []
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_global_graph_pool: Optional[Any] = None
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@property
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def supported_dtypes(self) -> list[torch.dtype]:
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"""Returns the supported dtypes for the current platform."""
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@ -539,10 +537,7 @@ class Platform:
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"""
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Return the global graph pool for this platform.
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"""
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cls = self.__class__
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if cls._global_graph_pool is None:
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cls._global_graph_pool = self.graph_pool_handle()
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return cls._global_graph_pool
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return self.graph_pool_handle()
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@classmethod
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def get_cu_count(cls, device_id: int = 0) -> int:
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@ -54,7 +54,7 @@ class UBatchWrapper:
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if runtime_mode is not CUDAGraphMode.NONE:
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self.cudagraph_wrapper = CUDAGraphWrapper(
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runnable, vllm_config, runtime_mode=runtime_mode)
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self.graph_pool = current_platform.get_global_graph_pool()
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self.graph_pool = current_platform.graph_pool_handle()
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def __getattr__(self, key: str):
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# allow accessing the attributes of the runnable.
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