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* 1.supplementary notes 2.delete dead code * fix bug of forward meta * Global modification of forward meta * fix vl model_runner bug
68 lines
2.7 KiB
Python
68 lines
2.7 KiB
Python
"""
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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from typing import Callable, Optional
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from paddle.jit.dy2static.utils import Backend
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from fastdeploy.config import FDConfig
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from fastdeploy.model_executor.graph_optimization.cudagraph_piecewise_backend import \
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CudaGraphPiecewiseBackend
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class GraphOptBackend:
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"""
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Integrated various graph optimization functions, including dynamic graph to static graph conversion,
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CINN compilation optimization, CudaGraph, and so on.
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"""
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fd_config: FDConfig
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cudagraph_piecewise_backend: Optional[CudaGraphPiecewiseBackend] = None
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def __init__(self, runnable: Callable, fd_config: FDConfig):
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self.runnable = runnable
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self.fd_config = fd_config
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self.max_captre_batch = fd_config.graph_opt_config.cudagraph_capture_sizes[
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0]
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if self.fd_config.graph_opt_config.graph_opt_level > 0:
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# 1. Prepare cuda grpah input buffers (contain output of subgraphs)
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# 2. Convert dynamic grpah to static graph
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from paddle.jit import sot
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backend = (Backend.CINN
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if self.fd_config.graph_opt_config.graph_opt_level > 1
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else Backend.PHI)
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self.runnable = sot.symbolic_translate(self.runnable,
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training=False,
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backend=backend)
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def __call__(self, **kwargs):
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if not self.fd_config.graph_opt_config.use_cudagraph:
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return self.runnable(**kwargs)
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if self.cudagraph_piecewise_backend is None:
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self.cudagraph_piecewise_backend = CudaGraphPiecewiseBackend(
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fd_config=self.fd_config, runnable=self.runnable)
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assert kwargs["forward_meta"].ids_remove_padding is not None
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batch_size = kwargs["forward_meta"].ids_remove_padding.shape[0]
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if ((not kwargs["forward_meta"].step_use_cudagraph)
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or (batch_size > self.max_captre_batch)):
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return self.runnable(**kwargs)
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else:
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return self.cudagraph_piecewise_backend.__call__(**kwargs)
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