send

Description

Sends data to a rank within a collective communication group.

Prototype

def send(tensor, sr_tag, dest_rank, group = "hccl_world_group")

Parameters

Parameter	Input/Output	Description
tensor	Input	TensorFlow tensor type. Atlas Training Series Product: The supported data types are int8, uint8, int16, uint16, int32, uint32, int64, uint64, float16, float32, and float64.
sr_tag	Input	An int. Message tag. The send/recv pairs with the same sr_tag can receive and send data.
dest_rank	Input	An int. Target node of data. rank indicates the rank ID in the group.
group	Input	A string containing a maximum of 128 bytes, including the end character. Group name, which can be a user-defined value or hccl_world_group.

Returns

None

Constraints

The caller rank must be within the range defined by the group argument passed to this API call. Otherwise, the API call fails.
To perform point-to-point data sending and receiving between ranks from different AI servers, the sending and receiving ranks must have the same physical ID of the Ascend AI Processor.
The sending and receiving functions must be used in pairs and depend on other operators in the graph.

Applicability

Atlas Training Series Product

Example

The following is only a code snippet and cannot be executed. For details about how to call the HCCL Python APIs to perform collective communication, see Sample Code.

from npu_bridge.npu_init import *
tensor = tf.random_uniform((1, 3), minval=1, maxval=10, dtype=tf.float32)
sr_tag = 0
dest_rank = 1
result = hccl_ops.send(tensor, sr_tag, dest_rank)

Parent topic: npu_bridge.hccl.hccl_ops