:key_length]attention_mask= self_attention_mask.unsqueeze(2 if self.config.multi_query else 1) ...
首先看一下Deepspeed的设计理念，主要还是分片，在这个角度上它和标准的模型并行的理解并无二致，但是比如...
MULTI GPU TRAINING WITH DDP (Single to Multi) Install 初始化 Training Model Checkpointing DeepSpeed Configuration 单机多卡 Resource Configuration (single-node) 最简单的 Example 实战 Reference 书接上文对 ZeRO 进行了详细的分析,但是 talk is cheap,今天开始我会陆续更新一些 DeepSpeed 框架的 Code-Level 的...
[pytorch distributed] 02 DDP 基本概念(Ring AllReduce,node,world,rank,参数服务器) 7424 14 20:42 App DeepSpeed优化器并行ZeRO1/2/3原理 #大模型 #分布式并行 #训练 2744 19 20:54 App 一行代码激活DeepSpeed,提升ChatGLM3-6B模型训练效率 浏览方式(推荐使用) 哔哩哔哩 你感兴趣的视频都在B站 打开信息...
有关更多详细信息,请参阅相应的论文:Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism(https://arxiv.org/abs/1909.08053)。 首先,我们讨论数据和环境设置,以及如何使用原始的Megatron-LM训练GPT-2模型。接下来,我们逐步介绍如何使用DeepSpeed使该模型运行。最后,我们演示使用...
Multi-GPU How many different machines will you use (use more than l for multi node training)? [1]: 1 Should distributed operatlons be checked while running for errors? This can avoid timeout issues but will be slover. fves/Nol: Do you wish to optinize your seript with torch dynano...
Distributed Training with Mixed Precision 16-bit mixed precision Single-GPU/Multi-GPU/Multi-Node Model Parallelism Support for Custom Model Parallelism Integration with Megatron-LM Pipeline Parallelism 3D Parallelism The Zero Redundancy Optimizer (ZeRO) ...
pythontrain.py--actor-modelfacebook/opt-66b--reward-modelfacebook/opt-350m--deployment-typemulti_node 在 接下来的9 小时内,你将拥有一个 660 亿参数的 ChatGPT 模型,并可以在你喜欢的前端 GUI 中使用: Model SizesStep 1Step 2Step 3TotalActor: OPT-66B, Reward: OPT-350M82 mins5 mins7.5hr9hr...
Distributed Training with Mixed Precision 16-bit mixed precision Single-GPU/Multi-GPU/Multi-Node Model Parallelism Support for Custom Model Parallelism Integration with Megatron-LM Pipeline Parallelism 3D Parallelism The Zero Redundancy Optimizer (ZeRO) Optimizer State and Gradient Partitioning Activatio...
pytorch-multi-gpu-training /ddp_train.py DISTRIBUTED COMMUNICATION PACKAGE - TORCH.DISTRIBUTED 代码文件:pytorch_DDP.py 单卡显存占用:3.12 G 单卡GPU使用率峰值:99% 训练时长(5 epoch):560 s 训练结果:准确率85%左右 代码启动命令(单机 4 GPU) ...