# 需要導入模塊: import tensorflow [as 別名]# 或者: from tensorflow importreduce_all[as 別名]defnext_inputs(self, time, outputs, state, sample_ids, stop_token_prediction, name=None):'''Stop on EOS. Otherwise, pass the last output as the next input and pass through state.'''withtf.nam...
# 需要导入模块: from tensorflow.compat import v1 [as 别名]# 或者: from tensorflow.compat.v1 importreduce_all[as 别名]defmake_outer_masks(self, outer_masks, input_pianorolls):"""Returns outer masks, if all zeros created by completion masking."""outer_masks = tf.to_float(outer_masks)# ...
import torch import torch_npu import os import torch.distributed as dist def all_reduce_func(): # rank = int(os.getenv('LOCAL_RANK')) dist.init_process_group(backend='hccl', init_method='env://') #,world_size=2 rank=rank, world_size=2, rank = dist.get_rank() torch.npu.set_de...
MPI reduceAll是一种消息传递接口(Message Passing Interface)的操作,用于在并行计算中进行全局归约操作。它允许多个进程将各自的数据进行归约操作,最终得到一个全局的结果。 MPI reduceAll的主要特点和优势包括: 自定义操作功能:MPI reduceAll允许开发人员自定义归约操作的功能,可以根据具体需求定义不同的操作,如求...
All-reduce All-reduce与reduce的区别就在于后者最后的结果是只保存在一个进程中,而All-reduce需要每个进程都有同样的结果。所以All-reduce一般包含scatter操作,所以有时候也会看到reduce-scatter这种说法,其实reduce-scatter可以看成是all reduce的一种实现方式 ...
在开始实现all_reduce之前,首先需要确定当前是否处于分布式训练环境中。可以通过如下代码进行检查: importtorchiftorch.distributed.is_initialized():print("当前处于分布式训练环境")else:print("当前未处于分布式训练环境") 1. 2. 3. 4. 5. 6. 2. 创建分布式进程组 ...
1、all_reduce:在forward的时候通过all_reduce同步计算结果;backward的时候不需要进行通信。 Zero3 forward 1、all_gather:通过all_gather收集所有rank上的模型参数切片,为了聚合参数,以数据并行的方式进行前向传播。 backward 1、all_gather:通过all_gather收集所有rank上的模型参数切片。 2、reduce_scatter:通过reduce...
[tflite-gpu] Add REDUCE_ALL && REDUCE_ANY to gpu_compatibility … 72047ef copybara-service bot force-pushed the exported_pr_698543205 branch from 1ad96b9 to 72047ef Compare November 21, 2024 23:35 Sign up for free to join this conversation on GitHub. Already have an account? Sign...
<!DOCTYPE html> MPI_Allreduce主要优化参数 算法序号 算法内容 算法简介 1 Recursive 节点内和节点间均采用Recursive Doubling算法。 2 Node-aware Recursive+Binomial 支持节点感知,节点内采用Binomial Tree算法,节点间采用Recursive Doubling算法。 3 Socket-aware Rec
Ytk-mp4j is a fast, user-friendly, cross-platform, multi-process, multi-thread collective message passing java library which includes gather, scatter, allgather, reduce-scatter, broadcast, reduce, allreduce communications for distributed machine learning. machine-learning openmp mpi reduce broadcast me...