o Me ã@s4ddlmmZddlmZdd„Zd dd„ZdS) éN)Ú collectivecCsF|durt ¡n|}|r|j ||¡S|j |||¡}|r!| ¡|S)N)rZ_get_default_groupZ process_groupZsend_on_calc_streamÚsendÚwait)ÚtensorÚdstÚgroupÚsync_opÚuse_calc_streamÚtask©r ú\D:\Projects\ConvertPro\env\Lib\site-packages\paddle/distributed/communication/stream/send.pyÚ_send_in_dygraphsr TFcCsH|dur | ¡s tdƒ‚|s|rtdƒ‚t ¡r t|||||ƒStdƒ‚)a  Send a tensor to the destination device. Args: tensor (Tensor): The tensor to send. Support float16, float32, float64, int32, int64, int8, uint8 or bool as its data type. dst (int, optional): Rank of the destination device. If none is given, use `0` as default. 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: .. code-block:: python # required: distributed 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]]) task = dist.stream.send(data, dst=1, sync_op=False) else: data = paddle.to_tensor([[1, 2, 3], [1, 2, 3]]) task = dist.stream.recv(data, src=0, sync_op=False) task.wait() out = data.numpy() # [[4, 5, 6], [4, 5, 6]] (2 GPUs) NzjThe group should not be None and all ranks which invoke this operation should be the member of this group.z5use_calc_stream can only be True in sync op behavior.zEpaddle.distributed.stream.send is only supported in dygraph mode now.)Z is_memberÚ RuntimeErrorÚ frameworkZin_dygraph_moder )rrrrr r r r rs&ÿÿÿr)rNTF)Zpaddle.fluid.frameworkZfluidrZpaddle.distributedrr rr r r r Ús