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mindspore.ops.Send

class mindspore.ops.Send(sr_tag, dest_rank, group=GlobalComm.WORLD_COMM_GROUP, group_back=GlobalComm.WORLD_COMM_GROUP)[source]

Send tensors to the specified dest_rank.

Note

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

Parameters
  • sr_tag (int) – The tag to identify the send/recv message. The message will be received by the Receive op with the same "sr_tag".

  • dest_rank (int) – A required integer identifying the destination rank.

  • 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.

Inputs:
  • input_x (Tensor) - The shape of tensor is (x1,x2,...,xR).

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 SendNet(nn.Cell):
>>>     def __init__(self):
>>>         super(SendNet, self).__init__()
>>>         self.depend = ops.Depend()
>>>         self.send = ops.Send(sr_tag=0, dest_rank=8, group="hccl_world_group")
>>>
>>>     def construct(self, x):
>>>         out = self.depend(x, self.send(x))
>>>         return out
>>>
>>> input_ = Tensor(np.ones([2, 8]).astype(np.float32))
>>> net = SendNet()
>>> output = net(input_)
Tutorial Examples: