receive

Applicability

Product	Supported
Atlas A3 training products/Atlas A3 inference products	√
Atlas A2 training products/Atlas A2 inference products	√
Atlas 200I/500 A2 inference products	☓
Atlas inference products	√
Atlas training products	√

For the Atlas inference products, only the Atlas 300I Duo inference card is supported.

Function Description

Receives data from a rank within a collective communication group.

Function Prototype

def receive(shape, data_type, sr_tag, src_rank, group="hccl_world_group")

Parameters

Option	Input/Output	Description
shape	Input	Shape of the received tensor.
data_type	Input	Data type of the received data. For the Atlas A3 training products/Atlas A3 inference products, the supported data types are int8, uint8, int16, uint16, int32, uint32, int64, uint64, float16, float32, float64, and bfp16. For the Atlas A2 training products/Atlas A2 inference products, the supported data types are int8, uint8, int16, uint16, int32, uint32, int64, uint64, float16, float32, float64, and bfp16. For the Atlas training products, the supported data types are int8, uint8, int16, uint16, int32, uint32, int64, uint64, float16, float32, and float64. For the Atlas 300I Duo inference card, the supported data types are int8, uint8, int16, uint16, int32, uint32, int64, uint64, float16, float32, and float64.
sr_tag	Input	Int type. Message tag. The send/recv pairs with the same sr_tag can receive and send data.
src_rank	Input	Int type. Source rank of the received data. This 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

The result tensor

Constraints

The caller rank must be within the range defined by the group argument passed to this API call. Otherwise, the API call fails.
The send and receive APIs must be used in pairs. That is, after the send API is called, the next API can be called only after the paired receive API receives data.

Example

from npu_bridge.hccl import hccl_ops
tensor = tf.random_uniform((1, 3), minval=1, maxval=10, dtype=tf.float32)
sr_tag = 0
src_rank = 0
tensor = hccl_ops.receive(tensor.shape, tensor.dtype, sr_tag, src_rank)

Parent topic: npu_bridge.hccl.hccl_ops