#   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.

# TODO: define random api
import paddle
from paddle import fluid
from paddle.fluid import core

__all__ = []


def seed(seed):
    """

    Sets the seed for global default generator, which manages the random number generation.

    Args:
        seed(int): The random seed to set. It is recommend to set a large int number.

    Returns:
        Generator: The global default generator object.

    Examples:
        .. code-block:: python

            >>> import paddle
            >>> gen = paddle.seed(102)

    """
    # TODO(zhiqiu): 1. remove program.random_seed when all random-related op upgrade
    # 2. support gpu generator by global device

    seed = int(seed)

    if core.is_compiled_with_cuda():
        for i in range(core.get_cuda_device_count()):
            core.default_cuda_generator(i).manual_seed(seed)
    elif core.is_compiled_with_xpu():
        for i in range(core.get_xpu_device_count()):
            core.default_xpu_generator(i).manual_seed(seed)
    place = fluid.framework._current_expected_place()
    if isinstance(place, core.CustomPlace):
        dev_cnt = sum(
            [
                place.get_device_type() == s.split(':')[0]
                for s in core.get_available_custom_device()
            ]
        )
        for i in range(dev_cnt):
            core.default_custom_device_generator(
                core.CustomPlace(place.get_device_type(), i)
            ).manual_seed(seed)
    return core.default_cpu_generator().manual_seed(seed)


def get_rng_state(device=None):
    """
    Get all random states of random generators of specified device.
    Args:
        device(str): This parameter determines the specific running device.
            It can be ``cpu``, ``gpu``, ``xpu``, Default is None.
            If None, return the generators of current device (specified by ``set_device``).
    Returns:
        GeneratorState:  object.
    Examples:
        .. code-block:: python
            >>> import paddle
            >>> sts = paddle.get_rng_state()
    """
    state_list = []
    if device is None:
        place = fluid.framework._current_expected_place()
    else:
        place = paddle.device._convert_to_place(device)

    if isinstance(place, core.CPUPlace):
        state_list.append(core.default_cpu_generator().get_state())
    elif isinstance(place, core.CUDAPlace):
        for i in range(core.get_cuda_device_count()):
            state_list.append(core.default_cuda_generator(i).get_state())
    elif isinstance(place, core.XPUPlace):
        for i in range(core.get_xpu_device_count()):
            state_list.append(core.default_xpu_generator(i).get_state())
    elif isinstance(place, core.CustomPlace):
        dev_cnt = sum(
            [
                place.get_device_type() == s.split(':')[0]
                for s in core.get_available_custom_device()
            ]
        )
        for i in range(dev_cnt):
            state_list.append(
                core.default_custom_device_generator(
                    core.CustomPlace(place.get_device_type(), i)
                ).get_state()
            )
    else:
        raise ValueError(
            "get_rng_state is not implemented for current device: {}".format(
                place
            )
        )

    return state_list


def get_cuda_rng_state():
    """

    Get random state of cuda generators.

    Args:
        None.

    Returns:
        GeneratorState:  object.

    Examples:
        .. code-block:: python

            >>> import paddle
            >>> sts = paddle.get_cuda_rng_state()

    """
    state_list = []
    if core.is_compiled_with_cuda():
        for i in range(core.get_cuda_device_count()):
            state_list.append(core.default_cuda_generator(i).get_state())

    return state_list


def set_rng_state(state_list, device=None):
    """

    Sets generator state for all device generators.

    Args:
        state_list(list|tuple): The device states to set back to device generators. state_list is obtained from get_rng_state().
        device(str): This parameter determines the specific running device.
            It can be ``cpu``, ``gpu``, ``xpu``, Default is None.
            If None, return the generators of current device (specified by ``set_device``).

    Returns:
        None.

    Examples:
        .. code-block:: python

            >>> import paddle
            >>> sts = paddle.get_rng_state()
            >>> paddle.set_rng_state(sts)

    """
    if device is None:
        place = fluid.framework._current_expected_place()
    else:
        place = device._convert_to_place(device)

    if isinstance(place, core.CUDAPlace):
        if not len(state_list) == core.get_cuda_device_count():
            raise ValueError(
                "Length of gpu state list shoule be equal to the gpu device count"
            )
        for i in range(core.get_cuda_device_count()):
            core.default_cuda_generator(i).set_state(state_list[i])
    elif isinstance(place, core.XPUPlace):
        if not len(state_list) == core.get_xpu_device_count():
            raise ValueError(
                "Length of xpu state list shoule be equal to the xpu device count"
            )
        for i in range(core.get_xpu_device_count()):
            core.default_xpu_generator(i).set_state(state_list[i])
    elif isinstance(place, core.CustomPlace):
        dev_cnt = sum(
            [
                place.get_device_type() == s.split(':')[0]
                for s in core.get_available_custom_device()
            ]
        )
        if not len(state_list) == dev_cnt:
            raise ValueError(
                f"Length of custom device state list shoule be equal to the {place.get_dtype_type()} device count"
            )
        for i in range(dev_cnt):
            core.default_custom_device_generator(
                core.CustomPlace(place.get_device_type(), i)
            ).set_state(state_list[i])
    elif isinstance(place, core.CPUPlace):
        if not len(state_list) == 1:
            raise ValueError("Length of cpu state list shoule be equal to 1")
        core.default_cpu_generator().set_state(state_list[0])
    else:
        raise ValueError(
            "set_rng_state is not implemented for current device: {}".format(
                place
            )
        )


def set_cuda_rng_state(state_list):
    """

    Sets generator state for all cuda generators.

    Args:
        state_list(list|tuple): The cuda states to set back to cuda generators. state_list is obtained from get_cuda_rng_state().

    Returns:
        None.

    Examples:
        .. code-block:: python

            >>> import paddle
            >>> sts = paddle.get_cuda_rng_state()
            >>> paddle.set_cuda_rng_state(sts)

    """
    if core.is_compiled_with_cuda():
        if not len(state_list) == core.get_cuda_device_count():
            raise ValueError(
                "Length of cuda state list shoule be equal to the cuda device count"
            )
        for i in range(core.get_cuda_device_count()):
            core.default_cuda_generator(i).set_state(state_list[i])


def _manual_program_seed(seed):
    """
    Sets global seed for generating random numbers.

    NOTE(zhiqiu): This is the original implemention of seed. Keeps it temporally
    since CUDA generator is not developed, so we need it in the unittest.

    Args:
        seed(int): The random seed to set. It is recommend to set a large int number.

    Returns:
        None
    """
    fluid.default_main_program().random_seed = seed
    fluid.default_startup_program().random_seed = seed
    program = fluid.Program()
    program.global_seed(seed)


def set_random_seed_generator(name, seed):
    core.set_random_seed_generator(name, seed)


def get_random_seed_generator(name):
    return core.get_random_seed_generator(name)
