Αi[SSKJr SSKJr SSKJrJr SSKJr SSK J r J r J r SSK Jr SSKJr \(aSSKJr SS KJr SS K Jr S rS rSSSjjrg )) annotations) TYPE_CHECKING)_C_ops framework) data_feeder)_get_global_group_get_or_throw_group_rank_warn_cur_rank_not_in_group)_to_inplace_op) in_pir_mode)Tensor)task)GroupcU(aURRX5$URRXU5nU(aUR"5 U$)N) process_groupbroadcast_on_calc_stream broadcastwait)tensorsrc_rank_in_groupgroupsync_opuse_calc_streamrs q/var/www/html/banglarbhumi/venv/lib/python3.13/site-packages/paddle/distributed/communication/stream/broadcast.py_broadcast_in_dygraphr#sN"";;       ( (G LD Kcj[R"US/SQS5 Sn[R"U40[ 5D6nUcSO UR n[ 5(a#[U5n[[U5"XX5 gURUSU/0SU/0UUS.S9nU(aS URl gg) Nr)float16float32float64int32int64int8uint8boolrrxout)rootring_id)typeinputsoutputsattrsdefault) rcheck_variable_and_dtyper LayerHelperlocalsidr r getattrr append_op dist_attrexecution_stream) rrrrrop_typehelperr)ops r_broadcast_in_static_moder:2s((   G  " "7 7fh 7F=aehhG}} ) 2CM    fX!%  B(1 %rNc[U5(agU(dU(a [S5e[R"5(a'Uc [ 5OUn[ X5n[ XX#U5$UbS5e[XX#U5$)a Broadcast a tensor to all devices. Args: 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|None, 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 >>> # doctest: +REQUIRES(env: 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]]) >>> else: ... data = paddle.to_tensor([[1, 2, 3], [1, 2, 3]]) >>> task = dist.stream.broadcast(data, src=1, sync_op=False) >>> task.wait() # type: ignore[union-attr] >>> out = data.numpy() >>> print(out) >>> # [[1, 2, 3], [1, 2, 3]] (2 GPUs) Nz5use_calc_stream can only be True in sync op behavior.z3Group can not be used in static graph mode for now.)r RuntimeErrorrin_dynamic_moderr rr:)rsrcrrrrs rrr[sX#5))  C    ""',}!#%4S@$ u  } A })   r)NTF) rr r>intrz Group | Nonerr%rr%returnz task | None) __future__rtypingrpaddlerr paddle.baser&paddle.distributed.communication.grouprr r 'paddle.distributed.communication.reducer paddle.frameworkr r paddle.base.corerrrr:rrrrJs# $# C(%< &2X! A A A  A  A  A  A r