wehub-resource-sync
112 lines
3.6 KiB
Python
112 lines
3.6 KiB
Python
# Copyright (c) 2026 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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"""CUDA graph APIs."""
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from __future__ import annotations
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from typing import TYPE_CHECKING
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from paddle import core, device as _paddle_device
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from paddle.device.cuda.graphs import (
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CUDAGraph,
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is_cuda_graph_supported,
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)
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if TYPE_CHECKING:
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from typing_extensions import Self
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from paddle.device import Stream
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__all__ = [
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"CUDAGraph",
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"graph",
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"graph_pool_handle",
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"is_cuda_graph_supported",
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]
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def graph_pool_handle() -> int:
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"""Return an opaque token usable as the ``pool`` argument of
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:meth:`CUDAGraph.capture_begin` or :class:`graph`. Graphs sharing the
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same token share an underlying memory pool.
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"""
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if not is_cuda_graph_supported():
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raise RuntimeError(
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"CUDA Graph is only supported on PaddlePaddle compiled with "
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"NVIDIA GPU."
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)
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return core.CUDAGraph.gen_new_memory_pool_id()
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class graph:
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"""Context manager that wraps a CUDA graph capture.
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Args:
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cuda_graph (CUDAGraph): The :class:`CUDAGraph` instance to capture into.
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pool (int, optional): Memory pool token from :func:`graph_pool_handle`
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or another graph's :meth:`CUDAGraph.pool`.
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stream (paddle.cuda.Stream, optional): CUDA stream to capture on.
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When ``None``, capture happens on the current stream.
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capture_error_mode (str, optional): One of ``'global'``,
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``'thread_local'``, ``'relaxed'``. When ``None`` (default) the
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underlying :class:`CUDAGraph`'s constructor ``mode`` is used.
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Examples:
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.. code-block:: pycon
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>>> # doctest: +REQUIRES(env:GPU)
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>>> import paddle
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>>> paddle.device.set_device('gpu')
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>>> g = paddle.cuda.CUDAGraph()
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>>> x = paddle.zeros([2, 3])
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>>> with paddle.cuda.graph(g):
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... y = x + 1
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>>> g.replay()
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"""
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def __init__(
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self,
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cuda_graph: CUDAGraph,
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pool: int | None = None,
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stream: Stream | None = None,
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capture_error_mode: str | None = None,
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) -> None:
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self.cuda_graph = cuda_graph
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self.pool = pool
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self.capture_stream = stream
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self.capture_error_mode = capture_error_mode
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self.stream_ctx = _paddle_device.stream(stream)
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def __enter__(self) -> Self:
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# Synchronize the graph's own device, not the process-wide current
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# device which may be CPU (synchronize rejects non-accelerator places).
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_paddle_device.synchronize(self.cuda_graph._place)
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_paddle_device.empty_cache()
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self.stream_ctx.__enter__()
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try:
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self.cuda_graph.capture_begin(
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pool=self.pool, capture_error_mode=self.capture_error_mode
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)
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except BaseException:
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self.stream_ctx.__exit__(None, None, None)
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raise
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return self
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def __exit__(self, *args: object) -> None:
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try:
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self.cuda_graph.capture_end()
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finally:
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self.stream_ctx.__exit__(*args)
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