wehub-resource-sync
306 lines
9.8 KiB
Python
306 lines
9.8 KiB
Python
# Copyright (c) 2020 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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from __future__ import annotations
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from typing import TYPE_CHECKING
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import paddle
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from paddle.base import core
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from paddle.utils.decorator_utils import param_one_alias
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if TYPE_CHECKING:
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from collections.abc import Sequence
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__all__ = []
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def seed(seed: int) -> paddle.base.core.Generator:
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"""
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Sets the seed for global default generator, which manages the random number generation.
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Args:
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seed(int): The random seed to set. It is recommend to set a large int number.
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Returns:
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Generator: The global default generator object.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> gen = paddle.seed(102)
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"""
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# TODO(zhiqiu): 1. remove program.random_seed when all random-related op upgrade
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# 2. support gpu generator by global device
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seed = int(seed)
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if paddle.is_compiled_with_cuda():
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for i in range(core.get_cuda_device_count()):
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core.default_cuda_generator(i).manual_seed(seed)
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elif paddle.is_compiled_with_xpu():
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for i in range(core.get_xpu_device_count()):
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core.default_xpu_generator(i).manual_seed(seed)
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place = paddle.framework._current_expected_place()
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if isinstance(place, paddle.CustomPlace):
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dev_cnt = sum(
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[
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place.get_device_type() == s.split(':')[0]
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for s in core.get_available_custom_device()
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]
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)
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for i in range(dev_cnt):
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core.default_custom_device_generator(
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paddle.CustomPlace(place.get_device_type(), i)
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).manual_seed(seed)
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return core.default_cpu_generator().manual_seed(seed)
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def get_rng_state(
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device: str | None = None,
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) -> list[core.GeneratorState]:
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"""
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Get all random states of random generators of specified device.
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Args:
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device(str): This parameter determines the specific running device.
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It can be ``cpu``, ``gpu``, ``xpu``, Default is None.
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If None, return the generators of current device (specified by ``set_device``).
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Returns:
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list[GeneratorState], object.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> sts = paddle.get_rng_state()
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"""
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state_list = []
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if device is None:
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place = paddle.framework._current_expected_place_()
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else:
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place = paddle.device._convert_to_place(device)
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if isinstance(place, paddle.CPUPlace):
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state_list.append(core.default_cpu_generator().get_state())
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elif isinstance(place, paddle.CUDAPlace):
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for i in range(core.get_cuda_device_count()):
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state_list.append(core.default_cuda_generator(i).get_state())
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elif isinstance(place, paddle.XPUPlace):
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for i in range(core.get_xpu_device_count()):
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state_list.append(core.default_xpu_generator(i).get_state())
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elif isinstance(place, paddle.CustomPlace):
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dev_cnt = sum(
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[
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place.get_device_type() == s.split(':')[0]
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for s in core.get_available_custom_device()
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]
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)
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for i in range(dev_cnt):
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state_list.append(
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core.default_custom_device_generator(
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core.CustomPlace(place.get_device_type(), i)
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).get_state()
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)
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else:
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raise ValueError(
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f"get_rng_state is not implemented for current device: {place}"
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)
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return state_list
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def get_cuda_rng_state() -> list[paddle.base.core.GeneratorState]:
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"""
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Get random state of cuda generators.
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Args:
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None.
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Returns:
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GeneratorState: object.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> sts = paddle.get_cuda_rng_state()
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"""
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state_list = []
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if paddle.is_compiled_with_cuda():
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for i in range(core.get_cuda_device_count()):
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state_list.append(core.default_cuda_generator(i).get_state())
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return state_list
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@param_one_alias(["state_list", "new_state"])
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def set_rng_state(
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state_list: Sequence[paddle.base.core.GeneratorState],
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device: str | None = None,
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) -> None:
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"""
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Sets generator state for all device generators.
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Args:
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state_list(list|tuple): The device states to set back to device generators. state_list is obtained from get_rng_state().
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Alias: ``new_state``.
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device(str): This parameter determines the specific running device.
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It can be ``cpu``, ``gpu``, ``xpu``, Default is None.
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If None, return the generators of current device (specified by ``set_device``).
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Returns:
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None.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> sts = paddle.get_rng_state()
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>>> paddle.set_rng_state(sts)
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"""
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if device is None:
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place = paddle.framework._current_expected_place_()
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else:
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place = paddle.device._convert_to_place(device)
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if isinstance(place, paddle.CUDAPlace):
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if not len(state_list) == core.get_cuda_device_count():
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raise ValueError(
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"Length of gpu state list should be equal to the gpu device count"
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)
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for i in range(core.get_cuda_device_count()):
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core.default_cuda_generator(i).set_state(state_list[i])
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elif isinstance(place, paddle.XPUPlace):
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if not len(state_list) == core.get_xpu_device_count():
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raise ValueError(
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"Length of xpu state list should be equal to the xpu device count"
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)
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for i in range(core.get_xpu_device_count()):
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core.default_xpu_generator(i).set_state(state_list[i])
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elif isinstance(place, paddle.CustomPlace):
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dev_types = core.get_all_custom_device_type()
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dev_type = dev_types[0]
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dev_cnt = core.get_custom_device_count(dev_type)
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if not len(state_list) == dev_cnt:
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raise ValueError(
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f"Length of custom device state list should be equal to the {dev_cnt} device count"
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)
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for i in range(dev_cnt):
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core.default_custom_device_generator(
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paddle.CustomPlace(place.get_device_type(), i)
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).set_state(state_list[i])
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elif isinstance(place, core.CPUPlace):
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if not len(state_list) == 1:
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raise ValueError("Length of cpu state list should be equal to 1")
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core.default_cpu_generator().set_state(state_list[0])
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else:
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raise ValueError(
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f"set_rng_state is not implemented for current device: {place}"
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)
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def set_cuda_rng_state(
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state_list: Sequence[paddle.base.core.GeneratorState],
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) -> None:
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"""
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Sets generator state for all cuda generators.
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Args:
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state_list(list|tuple): The cuda states to set back to cuda generators. state_list is obtained from get_cuda_rng_state().
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Returns:
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None.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> sts = paddle.get_cuda_rng_state()
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>>> paddle.set_cuda_rng_state(sts)
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"""
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if paddle.is_compiled_with_cuda():
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if not len(state_list) == core.get_cuda_device_count():
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raise ValueError(
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"Length of cuda state list should be equal to the cuda device count"
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)
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for i in range(core.get_cuda_device_count()):
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core.default_cuda_generator(i).set_state(state_list[i])
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def _manual_program_seed(seed: int) -> None:
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"""
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Sets global seed for generating random numbers.
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NOTE(zhiqiu): This is the original implementation of seed. Keeps it temporally
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since CUDA generator is not developed, so we need it in the unittest.
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Args:
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seed(int): The random seed to set. It is recommend to set a large int number.
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Returns:
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None
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"""
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paddle.static.default_main_program().random_seed = seed
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paddle.static.default_startup_program().random_seed = seed
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program = paddle.static.Program()
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program.global_seed(seed)
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def set_random_seed_generator(name: str, seed: int) -> None:
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core.set_random_seed_generator(name, seed)
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def get_random_seed_generator(name: str) -> paddle.base.core.Generator:
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return core.get_random_seed_generator(name)
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class Generator:
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def __new__(
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cls, device: str | int | paddle.core.Place = None
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) -> core.Generator:
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"""
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Generator is a random number generator.
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Args:
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device(str|int|paddle.core.Place): The device type to create the generator on.
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It can be ``cpu``, ``gpu``, ``xpu``, or a paddle.core.Place instance.
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default is None, which means using current device.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> g_cpu = paddle.Generator()
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"""
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place = paddle.device.device_to_place(device)
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if isinstance(place, core.CPUPlace):
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return core.default_cpu_generator()
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elif isinstance(place, core.CUDAPlace):
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return core.default_cuda_generator(place.gpu_device_id())
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elif isinstance(place, core.XPUPlace):
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return core.default_xpu_generator(place.gpu_device_id())
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elif isinstance(place, core.CustomPlace):
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return core.default_custom_device_generator(place)
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