Issue description I want use command "torchrun" to train my model on multiple GPU, but I need to set data parallel=1 in order to use sequence parallel. What should I do? cc @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @g...
并使用它们进行单机训练和评估。ModelScope 并未提供直接支持 DDP 的功能或教程。
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对于DP而言,输入到dataloader里面的batch_size参数指的是总的batch_size,例如batch_size=30,你有两块GPU,则每块GPU会吃15个sample;对于DDP而言,里面的batch_size参数指的却是每个GPU的batch_size,例如batch_size=30,你有两块GPU,则每块GPU会吃30个sample,一个batch总共就吃60个sample. 关于这点,使用上面的DP和...
ModelScope中的lora_ddp和lora_ddp_ds是微调大型预训练语言模型时使用的两种技术。以下是具体分析：...
load_checkpoint(args.model, None, None) unwrap_classes = (torchDDP, LocalDDP, MegatronFloat16Module) return unwrap_model(args.model, unwrap_classes)[0] def generate(self, input_ids=None, **kwargs): args = get_args() if parallel_state.get_data_parallel_world_size() > 1: ...
Autopilot also provides performance metrics for all of your candidate models. These metrics are calculated using all of the training data and are used to estimate model performance. The main working area includes these metrics by default. The type of metric is determined by the type of problem ...
This overview covers the basic theory behind diffusion modeling, through a breakdown of the “Real-World Denoising via Diffusion Model” paper
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@Mason1992-Git @tianlan6767 hi guys, you might encounter the case that there're no objects in one batch while training, which would lead a unused gradient error when you're training with DDP mode because the proto module in segment head is not returning gradients. Please uncomment the follow...