chore: import upstream snapshot with attribution

python/paddle/distributed/communication/all_reduce.py

@@ -0,0 +1,91 @@
+# 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.
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import paddle
+from paddle.distributed.communication import stream
+from paddle.distributed.communication.reduce import ReduceOp
+
+if TYPE_CHECKING:
+    from paddle import Tensor
+    from paddle.base.core import task
+    from paddle.distributed.communication.group import Group
+    from paddle.distributed.communication.reduce import _ReduceOp
+
+
+def all_reduce(
+    tensor: Tensor,
+    op: _ReduceOp = ReduceOp.SUM,
+    group: Group | None = None,
+    sync_op: bool = True,
+) -> task:
+    """
+
+    Reduce a tensor over all ranks so that all get the result.
+    As shown below, one process is started with a GPU and the data of this process is represented
+    by its group rank. The reduce operator is sum. Through all_reduce operator,
+    each GPU will have the sum of the data from all GPUs.
+
+    .. image:: https://githubraw.cdn.bcebos.com/PaddlePaddle/docs/develop/docs/api/paddle/distributed/img/allreduce.png
+        :width: 800
+        :alt: all_reduce
+        :align: center
+
+    Args:
+        tensor (Tensor): The input Tensor. It also works as the output Tensor. Its data type
+            should be float16, float32, float64, int32, int64, int8, uint8 or bool.
+        op (ReduceOp.SUM|ReduceOp.MAX|ReduceOp.MIN|ReduceOp.PROD|ReduceOp.AVG, optional): The operation used. Default value is ReduceOp.SUM.
+        group (Group|None, optional): The group instance return by new_group or None for global default group.
+        sync_op (bool, optional): Whether this op is a sync op. Default value is True.
+
+    Returns:
+        Return a task object.
+
+    Examples:
+        .. code-block:: pycon
+
+            >>> # doctest: +REQUIRES(env: DISTRIBUTED)
+            >>> import paddle
+            >>> import paddle.distributed as dist
+
+            >>> dist.init_parallel_env()
+            >>> if dist.get_rank() == 0:
+            ...     data = paddle.to_tensor([[4, 5, 6], [4, 5, 6]])
+            >>> else:
+            ...     data = paddle.to_tensor([[1, 2, 3], [1, 2, 3]])
+            >>> dist.all_reduce(data)
+            >>> print(data)
+            >>> # [[5, 7, 9], [5, 7, 9]] (2 GPUs)
+    """
+    # AVG is only supported when nccl >= 2.10
+    if op == ReduceOp.AVG and paddle.base.core.nccl_version() < 21000:
+        group = (
+            paddle.distributed.collective._get_global_group()
+            if group is None
+            else group
+        )
+        tensor.scale_(1.0 / group.nranks)
+        return stream.all_reduce(
+            tensor,
+            op=ReduceOp.SUM,
+            group=group,
+            sync_op=sync_op,
+            use_calc_stream=False,
+        )
+
+    return stream.all_reduce(
+        tensor, op=op, group=group, sync_op=sync_op, use_calc_stream=False
+    )