mindspore.ops.Receive

class mindspore.ops.Receive(sr_tag, src_rank, shape, dtype, group=GlobalComm.WORLD_COMM_GROUP, group_back=GlobalComm.WORLD_COMM_GROUP)[source]

Receive tensors from src_rank.

Note

Send and Receive must be used in combination and have same sr_tag.

Parameters

  • sr_tag (int) – A required integer identifying the send/recv message tag. The message will will be send by the Send op with the same "sr_tag".

  • src_rank (int) – A required integer identifying the source rank.

  • shape (list[int]) – A required list identifying the shape of the tensor to be received.

  • dtype (Type) – A required Type identifying the type of the tensor to be received. The supported types: int8/int16/int32/float16/float32.

  • group (str, optional) – The communication group to work on. Default: GlobalComm.WORLD_COMM_GROUP.

  • group_back (str, optional) – The communication group for backpropagation. Default: GlobalComm.WORLD_COMM_GROUP.

Outputs:

Tensor, output has the same shape as the Tensor sent by Send operation.

Raises

  • TypeError – If group is not a str.

  • RuntimeError – If device target is invalid, or backend is invalid, or distributed initialization fails.

  • ValueError – If the local rank id of the calling process in the group is larger than the group's rank size.

Supported Platforms:

Ascend GPU

Examples

Note

Before running the following examples, you need to configure the communication environment variables.

For Ascend/GPU/CPU devices, it is recommended to use the msrun startup method without any third-party or configuration file dependencies. Please see the msrun start up for more details.

This example should be run with 2 devices.

>>> import numpy as np
>>> import mindspore.nn as nn
>>> from mindspore.communication import init
>>> from mindspore import Tensor
>>> from mindspore import ops
>>>
>>> init()
>>> class ReceiveNet(nn.Cell):
>>>     def __init__(self):
>>>         super(ReceiveNet, self).__init__()
>>>         self.recv = ops.Receive(sr_tag=0, src_rank=0, shape=[2, 8], dtype=ms.float32,
>>>                               group="hccl_world_group")
>>>
>>>     def construct(self):
>>>         out = self.recv()
>>>         return out
>>>
>>> net = Net()
>>> output = net()
Tutorial Examples: