broadcast¶

paddle.distributed.communication.stream. broadcast ( tensor, src, group=None, sync_op=True, use_calc_stream=False ) [source]

Broadcast a tensor to all devices.

Parameters

tensor (Tensor) – The tensor to broadcast. Support float16, float32, float64, int32, int64, int8, uint8 or bool as its data type.
src (int, optional) – Rank of the source device.
group (Group, optional) – Communicate in which group. If none is given, use the global group as default.
sync_op (bool, optional) – Indicate whether the communication is sync or not. If none is given, use true as default.
use_calc_stream (bool, optional) – Indicate whether the communication is done on calculation stream. If none is given, use false as default. This option is designed for high performance demand, be careful to turn it on except you are clearly know its meaning.

Returns

Return a task object.

Warning

This API only supports the dygraph mode now.

Examples

           >>> 
>>> import paddle
>>> import paddle.distributed as dist

>>> dist.init_parallel_env()
>>> local_rank = dist.get_rank()
>>> if local_rank == 0:
...     data = paddle.to_tensor([[4, 5, 6], [4, 5, 6]])
>>> else:
...     data = paddle.to_tensor([[1, 2, 3], [1, 2, 3]])
>>> task = dist.stream.broadcast(data, src=1, sync_op=False)
>>> task.wait()
>>> out = data.numpy()
>>> print(out)
>>> # [[1, 2, 3], [1, 2, 3]] (2 GPUs)

          