apps/FastDeploy
1
0
Fork 0
mirror of https://github.com/PaddlePaddle/FastDeploy.git synced 2025-10-02 07:12:31 +08:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity

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

Browse Source
This commit is contained in:
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
Download Patch File Download Diff File Expand all files Collapse all files

33
fastdeploy/model_executor/graph_optimization/cudagraph_piecewise_backend.py
View File

@@ -17,19 +17,19 @@
from dataclasses import dataclass
from typing import Callable, Dict, Optional
import paddle.device.cuda.graphs as graphs
import paddle.nn.layer
from paddle.device.cuda import graphs
from fastdeploy.config import FDConfig
from fastdeploy.utils import get_logger
logger = get_logger("cudagrpah_piecewise_backend",
"cudagraph_piecewise_backend.log")
logger = get_logger("cudagrpah_piecewise_backend", "cudagraph_piecewise_backend.log")
@dataclass
class ConcreteSizeEntry:
""" Record the concrete information corresponding to the current batch size """
"""Record the concrete information corresponding to the current batch size"""
# Concrete batch size
runtime_bs: int
# The size is in cudagraph_capture_sizes
@@ -48,7 +48,7 @@ class ConcreteSizeEntry:
class CudaGraphPiecewiseBackend:
""" Manage the capture and replay of CUDA graphs at the subgraph level. """
"""Manage the capture and replay of CUDA graphs at the subgraph level."""
def __init__(
self,
@@ -65,12 +65,10 @@ class CudaGraphPiecewiseBackend:
self.concrete_size_entries: Dict[int, ConcreteSizeEntry] = {}
for shape in self.cudagraph_capture_sizes:
self.concrete_size_entries[shape] = ConcreteSizeEntry(
runtime_bs=shape)
self.concrete_size_entries[shape] = ConcreteSizeEntry(runtime_bs=shape)
logger.info(
f"[CUDA GRAPH] CUDAGraph capture list {self.cudagraph_capture_sizes}, "
"Created all batch sizes entry."
f"[CUDA GRAPH] CUDAGraph capture list {self.cudagraph_capture_sizes}, " "Created all batch sizes entry."
)
def __call__(self, **kwargs):
@@ -87,9 +85,7 @@ class CudaGraphPiecewiseBackend:
assert entry is not None, f"Batch size:{padding_batch_size} is not in cuda graph capture list."
if entry.runnable is None:
entry.runnable = self.runnable
logger.debug(
f"[CUDA GRAPH] New entry lazy initialize with batch size {padding_batch_size}"
)
logger.debug(f"[CUDA GRAPH] New entry lazy initialize with batch size {padding_batch_size}")
if not entry.use_cudagraph:
return entry.runnable(**kwargs)
@@ -106,10 +102,7 @@ class CudaGraphPiecewiseBackend:
)
# Store input addresses for debug
input_addresses = [
x.data_ptr() for (_, x) in kwargs.items()
if isinstance(x, paddle.Tensor)
]
input_addresses = [x.data_ptr() for (_, x) in kwargs.items() if isinstance(x, paddle.Tensor)]
entry.input_addresses = input_addresses
new_grpah = graphs.CUDAGraph()
@@ -127,13 +120,9 @@ class CudaGraphPiecewiseBackend:
output._clear
paddle.device.synchronize()
logger.debug(
f"[CUDA GRAPH] CUDAGraph captured for batch size {padding_batch_size}"
)
logger.debug(f"[CUDA GRAPH] CUDAGraph captured for batch size {padding_batch_size}")
# Replay
entry.cuda_graph.replay()
logger.debug(
f"[CUDA GRAPH] CUDAGraph replayed for batch size {padding_batch_size}"
)
logger.debug(f"[CUDA GRAPH] CUDAGraph replayed for batch size {padding_batch_size}")
return entry.output_buffer