# Copyright (c) 2022 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.

import paddle
import paddle.fluid.framework as framework
import paddle.distributed.communication.stream as stream


def send(tensor, dst=0, group=None, sync_op=True):
    """
    Send a tensor to the receiver.

    Args:
        tensor (Tensor): The Tensor to send. Its data type
            should be float16, float32, float64, int32, int64, int8, uint8, bool or bfloat16.
        dst (int): The destination rank id.
        group (Group, optional): The group instance return by new_group or None for global default group. Default: None.
        sync_op (bool, optional): Whether this op is a sync op. The default value is True.

    Returns:
        Return a task object.

    Examples:
        .. code-block:: python

            # required: distributed
            import paddle
            import paddle.distributed as dist

            dist.init_parallel_env()
            if dist.get_rank() == 0:
                data = paddle.to_tensor([7, 8, 9])
                dist.send(data, dst=1)
            else:
                data = paddle.to_tensor([1, 2, 3])
                dist.recv(data, src=0)
            print(data)
            # [7, 8, 9] (2 GPUs)
    """
    if not framework._in_legacy_dygraph():
        return stream.send(
            tensor, dst=dst, group=group, sync_op=sync_op, use_calc_stream=False
        )

    # code below will be removed after we remove the old dygraph
    if group is not None and not group.is_member():
        return
    use_calc_stream = sync_op
    gdst = dst if group is None else group.get_group_rank(dst)
    assert gdst >= 0, "dst rank out of group, need global rank"
    ring_id = 0 if group is None else group.id

    return paddle._legacy_C_ops.send_v2(
        tensor,
        'use_calc_stream',
        use_calc_stream,
        'ring_id',
        ring_id,
        'peer',
        gdst,
    )


def isend(tensor, dst, group=None):
    """
    Send tensor asynchronously

    Args:
        tensor (Tensor): The Tensor to send. Its data type
            should be float16, float32, float64, int32, int64, int8, uint8, bool or bfloat16.
        dst (int): The destination rank.
        group (Group, optional): The group instance return by new_group or None for global default group. Default: None.

    Returns:
        Return a task object.

    Warning:
        This API only supports the dygraph mode.

    Examples:
        .. code-block:: python

            # required: distributed
            import paddle
            import paddle.distributed as dist

            dist.init_parallel_env()
            if dist.get_rank() == 0:
                data = paddle.to_tensor([7, 8, 9])
                task = dist.isend(data, dst=1)
            else:
                data = paddle.to_tensor([1, 2, 3])
                task = dist.irecv(data, src=0)
            task.wait()
            print(data)
            # [7, 8, 9] (2 GPUs)

    """
    return send(tensor, dst, group, sync_op=False)