根据您提供的错误信息，问题出在megatron_util.mpu模块中没有找到get_model_parallel_rank属性。这可能是...
all_reduce(input_, group=get_tensor_model_parallel_group()) return input_ 测试代码 测试遵循文章【Megatron-DeepSpeed】张量并行工具代码mpu详解(一):并行环境初始化 中的设置,张量并行度为2,且流水线并行度为2。则张量并行组为:[Rank0, Rank1],[Rank2, Rank3],[Rank4,Rank5],[Rank6,Rank7]。
# Use both the tensor and pipeline MP rank. if pipeline_parallel is None: pipeline_parallel = (core.get_pipeline_model_parallel_world_size() > 1) pipeline_parallel = (mpu.get_pipeline_model_parallel_world_size() > 1) if tensor_rank is None: tensor_rank = core.get_tensor_model_parall...
(1)初始化全局变量:首先,mpu模块会初始化一系列全局变量,用于表示当前GPU的并行组信息,如_TENSOR_MODEL_PARALLEL_GROUP、_PIPELINE_MODEL_PARALLEL_GROUP等。 (2)计算并行组:基于用户设置的流水线并行度和张量并行度,mpu模块会计算出各个GPU所属的并行组。例如,Rank0和Rank4、Rank8、Rank12将属于同一个流水线并行...
mpu: Optional: A model parallelism unit object that implements get_model/data_parallel_group/rank/size() get_{model,data}_parallel_{rank,group,world_size}() dist_init_required: Optional: Initializes torch.distributed 3 changes: 2 additions & 1 deletion 3 docs/features.md Original file line...
DDR is set up with RTT_WR (also named dynamic ODT) and controlled by MR2[1:0] as follows: – MR2[1:0] = 0b00: disabled – MR2[1:0] = 0b01: 60 Ω– MR2[1:0] = 0b10: 120 Ω The DDR3 RTT_NOM mode is not used and not needed with single rank. The DQ/DQS output ...
简介:运行ZhipuAI/Multilingual-GLM-Summarization-zh的官方代码范例时,报错AttributeError: MGLMTextSummarizationPipeline: module 'megatron_util.mpu' has no attribute 'get_model_parallel_rank'环境是基于ModelScope官方docker镜像,尝试了各个版本结果都是一样的。
DDR is set up with RTT_WR (also named dynamic ODT) and controlled by MR2[1:0] as follows: – MR2[1:0] = 0b00: disabled – MR2[1:0] = 0b01: 60 Ω– MR2[1:0] = 0b10: 120 Ω The DDR3 RTT_NOM mode is not used and not needed with single rank. The DQ/DQS output ...
More specifically, the error occurs at the beginning of stage3.step where deepspeed is trying to get grad norm of gradients. Seems it doesn't correctly handle the scenario where some TP processes(model_parallel_rank > 0 ) has sub_group in self.fp16_groups which doesn't have parameters in...
if pipeline_parallel is None: pipeline_parallel = (mpu.get_pipeline_model_parallel_world_size() > 1) pipeline_parallel = (core.get_pipeline_model_parallel_world_size() > 1) if tensor_rank is None: tensor_rank = mpu.get_tensor_model_parallel_rank() tensor_rank = core.get_tensor_model...