mindspore2022/mindspore/communication/management.py

# Copyright 2020 Huawei Technologies Co., Ltd
#
# 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.
# ============================================================================
"""Communication management API"""
from mindspore import context
from mindspore.parallel._ps_context import _is_role_pserver, _is_role_sched
from ._comm_helper import Backend, _get_rank_helper, _get_size_helper, \
    _get_world_rank_from_group_rank_helper, _get_group_rank_from_world_rank_helper, \
    _create_group_helper, _destroy_group_helper, HCCL_WORLD_COMM_GROUP, NCCL_WORLD_COMM_GROUP, \
    _get_local_rank_helper, _get_local_size_helper, GlobalComm
from .._c_expression import init_hccl, finalize_hccl, init_gpu_collective


__all__ = ["init", "release", "get_rank", "get_local_rank", "get_group_size",
           "get_local_rank_size", "get_world_rank_from_group_rank",
           "get_group_rank_from_world_rank", "create_group", "destroy_group",
           "HCCL_WORLD_COMM_GROUP", "NCCL_WORLD_COMM_GROUP"]

DEFAULT_WORLD_COMM_GROUP = HCCL_WORLD_COMM_GROUP


def _get_group(group):
    """Return the world communication group if the `group` is `DEFAULT_WORLD_COMM_GROUP`."""
    if group == DEFAULT_WORLD_COMM_GROUP:
        return GlobalComm.WORLD_COMM_GROUP
    return group

def _check_task_sink_envs():
    """
    Check whether task_sink environment variables have been exported or not.

    return True if task_sink environment variables have been exported, False otherwise.
    """
    import os
    task_sink = os.getenv("GRAPH_OP_RUN")
    if task_sink:
        try:
            if int(task_sink) == 1:
                return False
        except ValueError:
            return True
    return True


def _check_parallel_envs():
    """
    Check whether parallel environment variables have been exported or not.

    Raises:
        RuntimeError: If parallel environment variables have not been exported or have been exported to wrong values.
    """
    if not GlobalComm.CHECK_ENVS:
        return
    import os
    rank_id_str = os.getenv("RANK_ID")
    if not rank_id_str:
        raise RuntimeError("Environment variables RANK_ID has not been exported")
    try:
        int(rank_id_str)
    except ValueError:
        print("RANK_ID should be number")
    rank_table_file_str = os.getenv("MINDSPORE_HCCL_CONFIG_PATH")
    rank_table_file_str_old = os.getenv("RANK_TABLE_FILE")
    if not rank_table_file_str and not rank_table_file_str_old:
        raise RuntimeError("Get hccl rank_table_file failed, "
                           "please export MINDSPORE_HCCL_CONFIG_PATH or RANK_TABLE_FILE.")

def init(backend_name=None):
    """
    Initialize distributed backend, e.g. HCCL/NCCL, it is required before using the communication service.

    Note:
        The full name of HCCL is Huawei Collective Communication Library.
        The full name of NCCL is NVIDIA Collective Communication Library.
        This method should be used after set_context.

    Args:
        backend_name (str): Backend, using HCCL/NCCL. if not been set, infer it by device_target. Default: None.

    Raises:
        TypeError: If `backend_name` is not a string.
        RuntimeError: If device target is invalid, or backend is invalid, or distributed initialization fails,
                      or the environment variables RANK_ID/MINDSPORE_HCCL_CONFIG_PATH
                      have not been exported when backend is HCCL.
        ValueError: If the environment variable RANK_ID has not been exported as a number.

    Examples:
        >>> from mindspore.context import set_context
        >>> set_context(device_target="Ascend")
        >>> init()
    """
    if _is_role_pserver() or _is_role_sched():
        return
    task_sink = _check_task_sink_envs()
    device_target = context.get_context("device_target")
    mode = context.get_context("mode")
    mpi_init = False
    if not task_sink and mode == context.GRAPH_MODE:
        mpi_init = True

    if backend_name is None:
        if device_target == "Ascend":
            backend_name = "hccl"
        elif device_target == "GPU":
            backend_name = "nccl"
        else:
            raise RuntimeError("Device target {} is not supported in parallel initialization, "
                               "please use Ascend or GPU.".format(device_target))
    if not isinstance(backend_name, str):
        raise TypeError("Backend name must be a string, but got {}".format(type(backend_name)))

    if backend_name == "hccl":
        if device_target != "Ascend":
            raise RuntimeError("Device target should be 'Ascend' to init hccl, but got {}".format(device_target))
        if not mpi_init:
            _check_parallel_envs()
            GlobalComm.BACKEND = Backend("hccl")
        else:
            GlobalComm.BACKEND = Backend("hccl_mpi")
        init_hccl()
        GlobalComm.WORLD_COMM_GROUP = HCCL_WORLD_COMM_GROUP
        GlobalComm.INITED = True
    elif backend_name == "nccl":
        init_gpu_collective()
        GlobalComm.BACKEND = Backend("nccl")
        GlobalComm.WORLD_COMM_GROUP = NCCL_WORLD_COMM_GROUP
        GlobalComm.INITED = True
    else:
        raise RuntimeError("Backend name {} is not supported.".format(backend_name))


def release():
    """
    Release distributed resource. e.g. HCCL/NCCL.

    Note:
        This method should be used after init().

    Raises:
        RuntimeError: If failed to release distributed resource.
    """
    finalize_hccl()


def get_rank(group=GlobalComm.WORLD_COMM_GROUP):
    """
    Get the rank ID for the current device in the specified collective communication group.

    Note:
        This method should be used after init().

    Args:
        group (str): The communication group to work on. Normally, the group should be created by create_group,
                     otherwise, using the default group. Default: WORLD_COMM_GROUP.

    Returns:
        int, the rank ID of the calling process within the group.

    Raises:
        TypeError: If group is not a string.
        ValueError: If backend is invalid.
        RuntimeError: If HCCL/NCCL is not available.
    """
    return _get_rank_helper(group=_get_group(group), backend=GlobalComm.BACKEND)


def get_local_rank(group=GlobalComm.WORLD_COMM_GROUP):
    """
    Gets local rank ID for current device in specified collective communication group.

    Note:
        GPU version of MindSpore doesn't support this method.
        This method should be used after init().

    Args:
        group (str): The communication group to work on. Normally, the group should be created by create_group,
                     otherwise, using the default group. Default: WORLD_COMM_GROUP.

    Returns:
        int, the local rank ID of the calling process within the group.

    Raises:
        TypeError: If group is not a string.
        ValueError: If backend is invalid.
        RuntimeError: If HCCL/NCCL is not available or MindSpore is GPU version.
    """
    return _get_local_rank_helper(group=_get_group(group), backend=GlobalComm.BACKEND)


def get_group_size(group=GlobalComm.WORLD_COMM_GROUP):
    """
    Get the rank size of the specified collective communication group.

    Note:
        This method should be used after init().

    Args:
        group (str): The communication group to work on. Normally, the group should be created by create_group,
                     otherwise, using the default group. Default: WORLD_COMM_GROUP.

    Returns:
        int, the rank size of the group.

    Raises:
        TypeError: If group is not a string.
        ValueError: If backend is invalid.
        RuntimeError: If HCCL/NCCL is not available.
    """
    return _get_size_helper(group=_get_group(group), backend=GlobalComm.BACKEND)


def get_local_rank_size(group=GlobalComm.WORLD_COMM_GROUP):
    """
    Gets local rank size of the specified collective communication group.

    Note:
        GPU version of MindSpore doesn't support this method.
        This method should be used after init().

    Args:
        group (str): The communication group to work on. The group is created by create_group
                     or the default world communication group. Default: WORLD_COMM_GROUP.

    Returns:
        int, the local rank size where the calling process is within the group.

    Raises:
        TypeError: If group is not a string.
        ValueError: If backend is invalid.
        RuntimeError: If HCCL/NCCL is not available or MindSpore is GPU version.
    """
    return _get_local_size_helper(group=_get_group(group), backend=GlobalComm.BACKEND)


def get_world_rank_from_group_rank(group, group_rank_id):
    """
    Get the rank ID in the world communication group corresponding to
    the rank ID in the specified user communication group.

    Note:
        GPU version of MindSpore doesn't support this method.
        The parameter group should not be "hccl_world_group".
        This method should be used after init().

    Args:
        group (str): The communication group to work on. The group is created by create_group.
        group_rank_id (int): A rank ID in the communication group.

    Returns:
        int, the rank ID in world communication group.

    Raises:
        TypeError: If `group_rank_id` is not an integer or the group is not a string.
        ValueError: If group is 'hccl_world_group' or backend is invalid.
        RuntimeError: If HCCL/NCCL is not available or MindSpore is GPU version.

    Examples:
        >>> from mindspore.context import set_context
        >>> set_context(device_target="Ascend")
        >>> init()
        >>> group = "0-4"
        >>> rank_ids = [0,4]
        >>> create_group(group, rank_ids)
        >>> world_rank_id = get_world_rank_from_group_rank(group, 1)
        >>> print("world_rank_id is: ", world_rank_id) # world_rank_id is: 4
    """
    return _get_world_rank_from_group_rank_helper(group=group, group_rank_id=group_rank_id, backend=GlobalComm.BACKEND)


def get_group_rank_from_world_rank(world_rank_id, group):
    """
    Get the rank ID in the specified user communication group corresponding to
    the rank ID in the world communication group.

    Note:
        GPU version of MindSpore doesn't support this method.
        The parameter group should not be "hccl_world_group".
        This method should be used after init().

    Args:
        world_rank_id (int): A rank ID in the world communication group.
        group (str): The communication group to work on. The group is created by create_group.

    Returns:
        int, the rank ID in the user communication group.

    Raises:
        TypeError: If world_rank_id is not an integer or the group is not a string.
        ValueError: If group is 'hccl_world_group' or backend is invalid.
        RuntimeError: If HCCL/NCCL is not available or MindSpore is GPU version.

    Examples:
        >>> from mindspore.context import set_context
        >>> set_context(device_target="Ascend")
        >>> init()
        >>> group = "0-4"
        >>> rank_ids = [0,4]
        >>> create_group(group, rank_ids)
        >>> group_rank_id = get_group_rank_from_world_rank(4, group)
        >>> print("group_rank_id is: ", group_rank_id) # group_rank_id is: 1
    """
    return _get_group_rank_from_world_rank_helper(world_rank_id=world_rank_id, group=group, backend=GlobalComm.BACKEND)


def create_group(group, rank_ids):
    """
    Create a user collective communication group.

    Note:
        GPU version of MindSpore doesn't support this method.
        The size of rank_ids should be larger than 1.
        Rank_ids should not have duplicate data.
        This method should be used after init().

    Args:
        group (str): The name of the communication group to be created.
        rank_ids (list): A list of device IDs.

    Raises:
        TypeError: If group is not a string or `rank_ids` is not a list.
        ValueError: If `rank_ids` size is not larger than 1, or `rank_ids` has duplicate data, or backend is invalid.
        RuntimeError: If hccl is not available or MindSpore is GPU version.

    Examples:
        >>> from mindspore.context import set_context
        >>> set_context(device_target="Ascend")
        >>> init()
        >>> group = "0-8"
        >>> rank_ids = [0,8]
        >>> create_group(group, rank_ids)
    """
    _create_group_helper(group, rank_ids, backend=GlobalComm.BACKEND)


def destroy_group(group):
    """
    Destroy the user collective communication group.

    Note:
        GPU version of MindSpore doesn't support this method.
        The parameter group should not be "hccl_world_group".
        This method should be used after init().

    Args:
        group (str): The communication group to destroy, the group should be created by create_group.

    Raises:
        TypeError: If group is not a string.
        ValueError: If group is "hccl_world_group" or backend is invalid.
        RuntimeError: If HCCL/NCCL is not available or MindSpore is GPU version.
    """
    _destroy_group_helper(group, backend=GlobalComm.BACKEND)