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polish code with new pre-commit rule (#2923)

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Zero Rains
2025-07-19 23:19:27 +08:00
committed by GitHub
parent b8676d71a8
commit 25698d56d1
424 changed files with 14307 additions and 13518 deletions
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23
fastdeploy/model_executor/graph_optimization/graph_optimization_backend.py
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@@ -19,8 +19,9 @@ from typing import Callable, Optional
from paddle.jit.dy2static.utils import Backend
from fastdeploy.config import FDConfig
from fastdeploy.model_executor.graph_optimization.cudagraph_piecewise_backend import \
CudaGraphPiecewiseBackend
from fastdeploy.model_executor.graph_optimization.cudagraph_piecewise_backend import (
CudaGraphPiecewiseBackend,
)
class GraphOptBackend:
@@ -36,32 +37,28 @@ class GraphOptBackend:
self.runnable = runnable
self.fd_config = fd_config
self.max_captre_batch = fd_config.graph_opt_config.cudagraph_capture_sizes[
0]
self.max_captre_batch = fd_config.graph_opt_config.cudagraph_capture_sizes[0]
if self.fd_config.graph_opt_config.graph_opt_level > 0:
# 1. Prepare cuda grpah input buffers (contain output of subgraphs)
# 2. Convert dynamic grpah to static graph
from paddle.jit import sot
backend = (Backend.CINN
if self.fd_config.graph_opt_config.graph_opt_level > 1
else Backend.PHI)
self.runnable = sot.symbolic_translate(self.runnable,
training=False,
backend=backend)
backend = Backend.CINN if self.fd_config.graph_opt_config.graph_opt_level > 1 else Backend.PHI
self.runnable = sot.symbolic_translate(self.runnable, training=False, backend=backend)
def __call__(self, **kwargs):
if not self.fd_config.graph_opt_config.use_cudagraph:
return self.runnable(**kwargs)
if self.cudagraph_piecewise_backend is None:
self.cudagraph_piecewise_backend = CudaGraphPiecewiseBackend(
fd_config=self.fd_config, runnable=self.runnable)
fd_config=self.fd_config, runnable=self.runnable
)
assert kwargs["forward_meta"].ids_remove_padding is not None
batch_size = kwargs["forward_meta"].ids_remove_padding.shape[0]
if ((not kwargs["forward_meta"].step_use_cudagraph)
or (batch_size > self.max_captre_batch)):
if (not kwargs["forward_meta"].step_use_cudagraph) or (batch_size > self.max_captre_batch):
return self.runnable(**kwargs)
else:
return self.cudagraph_piecewise_backend.__call__(**kwargs)