chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
@@ -0,0 +1,603 @@
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# Copyright (c) 2021 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, TypeAlias
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import paddle
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from paddle.base import core
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from .custom_streams import ( # noqa: F401
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Event,
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Stream,
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create_event,
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create_stream,
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)
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if TYPE_CHECKING:
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from paddle import CustomPlace
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_CustomPlaceLike: TypeAlias = (
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CustomPlace
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| str # some string like "iluvatar_gpu" "metax_gpu:0", etc.
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| int # some int like 0, 1, etc.
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)
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dev_types = core.get_all_custom_device_type()
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dev_type = dev_types[0] if dev_types else None
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if dev_type and not core.is_compiled_with_custom_device(dev_type):
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raise Exception(
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"No custom device available, please install paddle with custom device support"
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)
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if dev_type and dev_type in ['metax_gpu', 'iluvatar_gpu']:
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from .gpgpu_backend import get_device_properties
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else:
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from .default_backend import get_device_properties
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__all__ = [
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'Stream',
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'Event',
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'device_count',
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'get_device_properties',
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'empty_cache',
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'max_memory_allocated',
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'max_memory_reserved',
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'reset_max_memory_allocated',
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'reset_max_memory_reserved',
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'memory_allocated',
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'memory_reserved',
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'current_stream',
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'synchronize',
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]
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def device_count(device_type: str | None = None) -> int:
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'''
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Return the number of custom devices available.
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Args:
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device_type (str, optional): The type of custom device (e.g., 'npu', 'mlu', etc.).
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If None, returns the count of the first available custom device type.
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Returns:
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int: the number of custom devices available.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> paddle.device.device_count()
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>>> paddle.device.device_count('npu')
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'''
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if device_type:
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num = core.get_custom_device_count(device_type)
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else:
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num = core.get_custom_device_count(dev_type)
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return num
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def empty_cache() -> None:
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'''
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Releases idle cached memory held by the allocator so that those can be used in other GPU
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application and visible in device-specific tools.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> paddle.device.empty_cache()
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'''
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core.device_empty_cache()
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def max_memory_allocated(device: _CustomPlaceLike | None = None) -> int:
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'''
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Return the peak size of memory that is allocated to tensor of the given device.
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Args:
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device(_CustomPlaceLike, optional): Support input like 'npu:0', 'mlu', int, or CustomPlace.
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If None, the device is the first available custom device with index 0.
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Returns:
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int: The peak size of memory that is allocated to tensor of the given device, in bytes.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> paddle.device.max_memory_allocated('npu:0')
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>>> paddle.device.max_memory_allocated('npu')
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>>> paddle.device.max_memory_allocated(0)
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>>> paddle.device.max_memory_allocated(Paddle.CustomPlace('npu', 0))
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'''
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device_id = 0
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if device is None:
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device_id = 0
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elif isinstance(device, str):
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colon_idx = device.rfind(':')
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if colon_idx == -1:
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device_id = 0
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else:
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device_id_str = device[colon_idx + 1 :]
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if not device_id_str.isdigit():
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raise ValueError(
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f"Invalid device ID '{device_id_str}'. "
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f"After colon must be digits only. "
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"Example: 'npu:0'"
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)
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device_id = int(device_id_str)
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elif isinstance(device, int):
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device_id = device
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elif isinstance(device, core.CustomPlace):
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device_id = device.get_device_id()
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else:
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raise ValueError(
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f"The input: {device} is not expected. Because paddle.device."
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"max_memory_allocated only support str, int or CustomPlace. "
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"Please input appropriate device again! "
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"Example: 'npu:0'"
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)
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return core.device_memory_stat_peak_value("Allocated", device_id)
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def max_memory_reserved(device: _CustomPlaceLike | None = None) -> int:
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'''
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Return the peak size of memory that is held by the allocator of the given device.
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Args:
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device(_CustomPlaceLike, optional): Support input like 'npu:0', 'mlu', int, or CustomPlace.
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If None, the device is the first available custom device with index 0.
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Returns:
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int: The peak size of memory that is held by the allocator of the given device, in bytes.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> paddle.device.max_memory_reserved('npu:0')
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>>> paddle.device.max_memory_reserved('npu')
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>>> paddle.device.max_memory_reserved(0)
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>>> paddle.device.max_memory_reserved(Paddle.CustomPlace('npu', 0))
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'''
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device_id = 0
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if device is None:
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device_id = 0
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elif isinstance(device, str):
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colon_idx = device.rfind(':')
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if colon_idx == -1:
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device_id = 0
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else:
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device_id_str = device[colon_idx + 1 :]
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if not device_id_str.isdigit():
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raise ValueError(
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f"Invalid device ID '{device_id_str}'. "
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f"After colon must be digits only. "
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"Example: 'npu:0'"
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)
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device_id = int(device_id_str)
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elif isinstance(device, int):
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device_id = device
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elif isinstance(device, core.CustomPlace):
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device_id = device.get_device_id()
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else:
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raise ValueError(
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f"The input: {device} is not expected. Because paddle.device."
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"max_memory_reserved only support str, int or CustomPlace. "
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"Please input appropriate device again! "
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"Example: 'npu:0'"
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)
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return core.device_memory_stat_peak_value("Reserved", device_id)
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def reset_max_memory_allocated(device: _CustomPlaceLike | None = None) -> None:
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'''
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Reset the peak size of memory that is allocated to tensor of the given device.
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Args:
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device(_CustomPlaceLike, optional): Support input like 'npu:0', 'mlu', int, or CustomPlace.
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If None, the device is the first available custom device with index 0.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> paddle.device.reset_max_memory_allocated('npu:0')
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>>> paddle.device.reset_max_memory_allocated('npu')
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>>> paddle.device.reset_max_memory_allocated(0)
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>>> paddle.device.reset_max_memory_allocated(Paddle.CustomPlace('npu', 0))
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'''
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device_id = 0
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if device is None:
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device_id = 0
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elif isinstance(device, str):
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colon_idx = device.rfind(':')
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if colon_idx == -1:
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device_id = 0
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else:
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device_id_str = device[colon_idx + 1 :]
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if not device_id_str.isdigit():
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raise ValueError(
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f"Invalid device ID '{device_id_str}'. "
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f"After colon must be digits only. "
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"Example: 'npu:0'"
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)
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device_id = int(device_id_str)
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elif isinstance(device, int):
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device_id = device
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elif isinstance(device, core.CustomPlace):
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device_id = device.get_device_id()
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else:
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raise ValueError(
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f"The input: {device} is not expected. Because paddle.device."
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"reset_max_memory_allocated only support str, int or CustomPlace. "
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"Please input appropriate device again! "
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"Example: 'npu:0'"
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)
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core.device_memory_stat_reset_peak_value("Allocated", device_id)
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def reset_max_memory_reserved(device: _CustomPlaceLike | None = None) -> None:
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'''
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Reset the peak size of memory that is held by the allocator of the given device.
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Args:
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device(_CustomPlaceLike, optional): Support input like 'npu:0', 'mlu', int, or CustomPlace.
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If None, the device is the first available custom device with index 0.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> paddle.device.reset_max_memory_reserved('npu:0')
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>>> paddle.device.reset_max_memory_reserved('npu')
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>>> paddle.device.reset_max_memory_reserved(0)
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>>> paddle.device.reset_max_memory_reserved(Paddle.CustomPlace('npu', 0))
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'''
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device_id = 0
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if device is None:
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device_id = 0
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elif isinstance(device, str):
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colon_idx = device.rfind(':')
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if colon_idx == -1:
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device_id = 0
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else:
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device_id_str = device[colon_idx + 1 :]
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if not device_id_str.isdigit():
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raise ValueError(
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f"Invalid device ID '{device_id_str}'. "
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f"After colon must be digits only. "
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"Example: 'npu:0'"
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)
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device_id = int(device_id_str)
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elif isinstance(device, int):
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device_id = device
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elif isinstance(device, core.CustomPlace):
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device_id = device.get_device_id()
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else:
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raise ValueError(
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f"The input: {device} is not expected. Because paddle.device."
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"reset_max_memory_reserved only support str, int or CustomPlace. "
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"Please input appropriate device again! "
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"Example: 'npu:0'"
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)
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core.device_memory_stat_reset_peak_value("Reserved", device_id)
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def memory_allocated(device: _CustomPlaceLike | None = None) -> int:
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'''
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Return the current size of memory that is allocated to tensor of the given device.
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Args:
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device(_CustomPlaceLike, optional): Support input like 'npu:0', 'mlu', int, or CustomPlace.
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If None, the device is the first available custom device with index 0.
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Returns:
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int: The current size of memory that is allocated to tensor of the given device, in bytes.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> paddle.device.memory_allocated('npu:0')
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>>> paddle.device.memory_allocated('npu')
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>>> paddle.device.memory_allocated(0)
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>>> paddle.device.memory_allocated(Paddle.CustomPlace('npu', 0))
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'''
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device_id = 0
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if device is None:
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device_id = 0
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elif isinstance(device, str):
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colon_idx = device.rfind(':')
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if colon_idx == -1:
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device_id = 0
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else:
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device_id_str = device[colon_idx + 1 :]
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if not device_id_str.isdigit():
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raise ValueError(
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f"Invalid device ID '{device_id_str}'. "
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f"After colon must be digits only. "
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"Example: 'npu:0'"
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)
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device_id = int(device_id_str)
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elif isinstance(device, int):
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device_id = device
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elif isinstance(device, core.CustomPlace):
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device_id = device.get_device_id()
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else:
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raise ValueError(
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f"The input: {device} is not expected. Because paddle.device."
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"memory_allocated only support str, int or CustomPlace. "
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"Please input appropriate device again! "
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"Example: 'npu:0'"
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)
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return core.device_memory_stat_current_value("Allocated", device_id)
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def memory_reserved(device: _CustomPlaceLike | None = None) -> int:
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'''
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Return the current size of memory that is held by the allocator of the given device.
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Args:
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device(_CustomPlaceLike, optional): Support input like 'npu:0', 'mlu', int, or CustomPlace.
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If None, the device is the first available custom device with index 0.
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Returns:
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int: The current size of memory that is held by the allocator of the given device, in bytes.
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Examples:
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.. code-block:: pycon
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>>> import paddle
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>>> paddle.device.memory_reserved('npu:0')
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>>> paddle.device.memory_reserved('npu')
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>>> paddle.device.memory_reserved(0)
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>>> paddle.device.memory_reserved(Paddle.CustomPlace('npu', 0))
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'''
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device_id = 0
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if device is None:
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device_id = 0
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elif isinstance(device, str):
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colon_idx = device.rfind(':')
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if colon_idx == -1:
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device_id = 0
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else:
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device_id_str = device[colon_idx + 1 :]
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if not device_id_str.isdigit():
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raise ValueError(
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f"Invalid device ID '{device_id_str}'. "
|
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f"After colon must be digits only. "
|
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"Example: 'npu:0'"
|
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)
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device_id = int(device_id_str)
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elif isinstance(device, int):
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device_id = device
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elif isinstance(device, core.CustomPlace):
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device_id = device.get_device_id()
|
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else:
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raise ValueError(
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f"The input: {device} is not expected. Because paddle.device."
|
||||
"memory_reserved only support str, int or CustomPlace. "
|
||||
"Please input appropriate device again! "
|
||||
"Example: 'npu:0'"
|
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)
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return core.device_memory_stat_current_value("Reserved", device_id)
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def current_stream(device: _CustomPlaceLike | None = None) -> core.CustomStream:
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'''
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Return the current stream by the device.
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Args:
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device(_CustomPlaceLike, optional): Support input like 'npu:0', 'mlu', int, or CustomPlace.
|
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If None, the device is the first available custom device with index 0.
|
||||
|
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Returns:
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Stream: The stream to the device.
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Examples:
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||||
.. code-block:: pycon
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||||
|
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>>> import paddle
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>>> paddle.device.current_stream('npu:0')
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>>> paddle.device.current_stream('npu')
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>>> paddle.device.current_stream(0)
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>>> paddle.device.current_stream(Paddle.CustomPlace('npu', 0))
|
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'''
|
||||
device_id = 0
|
||||
|
||||
if device is None:
|
||||
device_id = 0
|
||||
elif isinstance(device, str):
|
||||
colon_idx = device.rfind(':')
|
||||
if colon_idx == -1:
|
||||
device_id = 0
|
||||
else:
|
||||
device_id_str = device[colon_idx + 1 :]
|
||||
if not device_id_str.isdigit():
|
||||
raise ValueError(
|
||||
f"Invalid device ID '{device_id_str}'. "
|
||||
f"After colon must be digits only. "
|
||||
"Example: 'npu:0'"
|
||||
)
|
||||
device_id = int(device_id_str)
|
||||
elif isinstance(device, int):
|
||||
device_id = device
|
||||
elif isinstance(device, core.CustomPlace):
|
||||
device_id = device.get_device_id()
|
||||
else:
|
||||
raise ValueError(
|
||||
f"The input: {device} is not expected. Because paddle.device."
|
||||
"current_stream only support str, int or CustomPlace. "
|
||||
"Please input appropriate device again! "
|
||||
"Example: 'npu:0'"
|
||||
)
|
||||
|
||||
return core._get_current_custom_device_stream(dev_type, device_id)
|
||||
|
||||
|
||||
def synchronize(device: _CustomPlaceLike | None = None) -> None:
|
||||
"""
|
||||
Wait for the compute on the given device to finish.
|
||||
|
||||
Args:
|
||||
device(_CustomPlaceLike, optional): Support input like 'npu:0', 'mlu', int, or CustomPlace.
|
||||
If None, the device is the first available custom device with index 0.
|
||||
|
||||
Examples:
|
||||
.. code-block:: pycon
|
||||
|
||||
>>> import paddle
|
||||
>>> paddle.device.synchronize('npu:0')
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||||
>>> paddle.device.synchronize('npu')
|
||||
>>> paddle.device.synchronize(0)
|
||||
>>> paddle.device.synchronize(Paddle.CustomPlace('npu', 0))
|
||||
"""
|
||||
device_id = 0
|
||||
|
||||
if device is None:
|
||||
device_id = 0
|
||||
elif isinstance(device, str):
|
||||
colon_idx = device.rfind(':')
|
||||
if colon_idx == -1:
|
||||
device_id = 0
|
||||
else:
|
||||
device_id_str = device[colon_idx + 1 :]
|
||||
if not device_id_str.isdigit():
|
||||
raise ValueError(
|
||||
f"Invalid device ID '{device_id_str}'. "
|
||||
f"After colon must be digits only. "
|
||||
"Example: 'npu:0'"
|
||||
)
|
||||
device_id = int(device_id_str)
|
||||
elif isinstance(device, int):
|
||||
device_id = device
|
||||
elif isinstance(device, core.CustomPlace):
|
||||
device_id = device.get_device_id()
|
||||
else:
|
||||
raise ValueError(
|
||||
f"The input: {device} is not expected. Because paddle.device."
|
||||
"synchronize only support str, int or CustomPlace. "
|
||||
"Please input appropriate device again! "
|
||||
"Example: 'npu:0'"
|
||||
)
|
||||
|
||||
core._synchronize_custom_device(dev_type, device_id)
|
||||
|
||||
|
||||
def get_rng_state(
|
||||
device: _CustomPlaceLike | None = None,
|
||||
) -> core.GeneratorState:
|
||||
r'''
|
||||
Get the random state for the default generator.
|
||||
|
||||
Returns:
|
||||
Tensor: The random state tensor.
|
||||
|
||||
Examples:
|
||||
|
||||
.. code-block:: pycon
|
||||
|
||||
>>> # doctest: +REQUIRES(env:CUSTOM_DEVICE)
|
||||
>>> import paddle
|
||||
>>> paddle.device.get_rng_state()
|
||||
|
||||
'''
|
||||
place = paddle.device.device_to_place(device)
|
||||
if isinstance(place, core.CPUPlace):
|
||||
return core.default_cpu_generator().get_state()
|
||||
return core.default_custom_device_generator(place).get_state()
|
||||
|
||||
|
||||
def set_rng_state(
|
||||
new_state: core.GeneratorState, device: _CustomPlaceLike | None = None
|
||||
) -> None:
|
||||
"""
|
||||
Set the random number generator state of the specified device.
|
||||
|
||||
Args:
|
||||
new_state (core.GeneratorState): The desired RNG state to set.
|
||||
This should be a state object previously obtained from ``get_rng_state()``.
|
||||
device (DeviceLike, optional): The device to set the RNG state for.
|
||||
If not specified, uses the current default device (as returned by ``paddle.framework._current_expected_place_()``).
|
||||
Can be a device object, integer device ID, or device string.
|
||||
|
||||
Returns:
|
||||
None
|
||||
|
||||
Examples:
|
||||
.. code-block:: pycon
|
||||
|
||||
>>> import paddle
|
||||
>>> # Save RNG state
|
||||
>>> state = paddle.device.get_rng_state()
|
||||
>>> # Do some random operations
|
||||
>>> x = paddle.randn([2, 3])
|
||||
>>> # Restore RNG state
|
||||
>>> paddle.device.set_rng_state(state)
|
||||
"""
|
||||
place = paddle.device.device_to_place(device)
|
||||
if isinstance(place, core.CPUPlace):
|
||||
core.default_cpu_generator().set_state(new_state)
|
||||
else:
|
||||
core.default_custom_device_generator(place).set_state(new_state)
|
||||
|
||||
|
||||
def manual_seed(seed: int) -> None:
|
||||
r"""Set the seed for generating random numbers for the current Device.
|
||||
|
||||
.. warning::
|
||||
If you are working with a multi-Device model, this function is insufficient
|
||||
to get determinism. To seed all Devices, use :func:`manual_seed_all`.
|
||||
If current Device is CPU, this function will set the seed of the default CPU generator.
|
||||
|
||||
Sets the seed for global default generator, which manages the random number generation.
|
||||
|
||||
Args:
|
||||
seed(int): The random seed to set.
|
||||
|
||||
Returns:
|
||||
None
|
||||
|
||||
Examples:
|
||||
.. code-block:: pycon
|
||||
|
||||
>>> # doctest: +REQUIRES(env:CUSTOM_DEVICE)
|
||||
>>> import paddle
|
||||
>>> paddle.device.manual_seed(102)
|
||||
>>> # paddle.cuda.manual_seed(102) is equivalent to paddle.device.manual_seed(102)
|
||||
|
||||
"""
|
||||
seed = int(seed)
|
||||
place = paddle.framework._current_expected_place()
|
||||
if isinstance(place, core.CPUPlace):
|
||||
core.default_cpu_generator().manual_seed(seed)
|
||||
else:
|
||||
core.default_custom_device_generator(place).manual_seed(seed)
|
||||
Reference in New Issue
Block a user