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[CUDAGraph]CUDA Graph support unique memory pool (#4230)
* cuda graph use unique memory pool * fix custom device import bug * refine code * refine code * refine code
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@@ -841,8 +841,13 @@ class GraphOptimizationConfig:
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Now don't support capture both decode-only and prefill-only"""
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self.full_cuda_graph: bool = True
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""" Maximum CUDA Graph capture size """
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self.max_capture_size: int = None
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""" Record maps mapped from real shape to captured size to reduce runtime overhead """
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self.real_shape_to_captured_size: dict[int, int] = None
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""" Whether to use shared memory pool for multi capture_size """
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self.use_unique_memory_pool: bool = False
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# CINN Config ...
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if args is not None:
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for key, value in args.items():
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@@ -96,6 +96,13 @@ class CudaGraphPiecewiseBackend:
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self.cudagraph_capture_sizes = fd_config.graph_opt_config.cudagraph_capture_sizes
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self.warm_up_size = fd_config.graph_opt_config.cudagraph_num_of_warmups
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self.real_shape_to_captured_size = fd_config.graph_opt_config.real_shape_to_captured_size
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self.unique_memory_pool_id = None
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if self.fd_config.graph_opt_config.use_unique_memory_pool:
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# TODO(gongshaotian): Optimize code
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if paddle.is_compiled_with_cuda():
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from paddle.base.core import CUDAGraph
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self.unique_memory_pool_id = CUDAGraph.gen_new_memory_pool_id()
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self._create_entry_dict()
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@@ -169,7 +176,7 @@ class CudaGraphPiecewiseBackend:
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input_addresses = [x.data_ptr() for (_, x) in kwargs.items() if isinstance(x, paddle.Tensor)]
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entry.input_addresses = input_addresses
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new_grpah = graphs.CUDAGraph()
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new_grpah = graphs.CUDAGraph(pool_id=self.unique_memory_pool_id)
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paddle.device.synchronize()
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# Capture
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