device.py

#   Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from paddle.fluid import core
from paddle.fluid import framework
import re
__all__ = [
    'set_device',
    'get_device'
    #            'cpu_places',
    #            'CPUPlace',
    #            'cuda_pinned_places',
    #            'cuda_places',
    #            'CUDAPinnedPlace',
    #            'CUDAPlace',
    #            'is_compiled_with_cuda'
]


def set_device(device):
    """
    Paddle supports running calculations on various types of devices, including CPU and GPU.
    They are represented by string identifiers. This function can specify the global device
    which the OP will run.

    Parameters:
        device(str): This parameter determines the specific running device.
            It can be ``cpu`` or ``gpu:0``. When ``device`` is ``cpu``, the
            program is running on the cpu. When ``device`` is ``gpu``, the
            program is running ont the gpu.
    Examples:

     .. code-block:: python
            
        import paddle
        paddle.enable_imperative()
        paddle.fluid.dygraph.set_device("gpu:0")
        x1 = paddle.ones(name='x1', shape=[1, 2], dtype='int32')
        x2 = paddle.zeros(name='x2', shape=[1, 2], dtype='int32')
        data = paddle.stack([x1,x2], axis=1)
    """
    lower_device = device.lower()
    if lower_device == 'cpu':
        place = core.CPUPlace()
        framework._set_expected_place(place)
    else:
        avaliable_device = ((lower_device == 'cpu') or
                            re.match(r'gpu:\d+', lower_device))
        if not avaliable_device:
            raise ValueError(
                "The device must be a string which is like 'cpu' or 'gpu:0'")
        device_info_list = device.split(':', 1)
        device_id = device_info_list[1]
        device_id = int(device_id)
        place = core.CUDAPlace(device_id)
        framework._set_expected_place(place)


def get_device():
    """
    This funciton can get the current global device of the program is running.
    It's a string which is like 'cpu' and 'gpu:0'. if the global device is not
    set, it will return a string which is 'gpu:0' when cuda is avaliable or it 
    will return a string which is 'cpu' when cuda is not avaliable.

    Examples:

     .. code-block:: python
            
        import paddle
        paddle.enable_imperative()
        device = paddle.fluid.dygraph.get_device()

    """
    device = ''
    place = framework._current_expected_place()
    if isinstance(place, core.CPUPlace):
        device = 'cpu'
    elif isinstance(place, core.CUDAPlace):
        device_id = place.get_device_id()
        device = 'gpu:' + str(device_id)

    return device