Device 3 - ZeRO Stage: 0 Device 6 - ZeRO Stage: 0 Device 7 - ZeRO Stage: 0 Device 0 - ZeRO Stage: 0 Device 5 - ZeRO Stage: 0 实际上,deepspeed 会在初始化过程中,创造多个进程,每个进程运行在一张 GPU 上,在deepspeed_config中,如果我们不显示的指定 zero-stage,将默认使用 stage 0. 我们...
ZeRo3参数{ "zero_optimization": { "stage": 3, "offload_optimizer": { "device": "cpu", "pin_memory": true }, "offload_param": { "device": "cpu", "pin_memory": true }, "overlap_comm": true, "contiguous_gradients": true, "sub_group_size": 1e9, //会把参数分组,在参数更新时...
通过使用ZeRO Stage1将优化器状态在八个数据并行 rank 之间进行切分,每个设备的内存消耗可以降低到2.25GB,从而使得模型可训练。为了启用ZeRO Stage1,我们只需要更新DeepSpeed JSON配置文件如下: { "zero_optimization": { "stage": 1, "reduce_bucket_size": 5e8 } } 如上所示,我们在zero_optimization键中设置了...
We implemented ZeRO stage one — optimizer states partitioning (ZeRO-OS in short) — which has a demonstrated capability to support 100-billion-parameter models. The code is being released together with our training optimization library, DeepSpeed. DeepSpeed brings state-o...
DeepSpeed 是由微软开发的开源深度学习优化库,旨在提高大规模模型训练的效率和可扩展性。通过创新的并行化策略、内存优化技术(如 ZeRO)及混合精度训练,DeepSpeed 显著提升了训练速度并降低了资源需求。它支持多种并行方法,包括数据并行、模型并行和流水线并行,同时与
We implemented ZeRO stage one — optimizer states partitioning (ZeRO-OS in short) — which has a demonstrated capability to support 100-billion-parameter models. The code is being released together with our training optimization library, DeepSpeed. DeepSpeed brings state-of-t...
},"zero_optimization": {"stage": 2} } deepseed安装好后,直接一行命令就开始运行:deepspeed ds_train.py --epoch 2 --deepspeed --deepspeed_config ds_config.json ;从日志可以看出:有几块显卡就会生成几个进程并发训练;显卡之间使用nccl互相通信; ...
"zero_optimization": { "stage": 2, "offload_param": true, "offload_optimizer": false, "offload_activations": true, "overlap_comm": true }, "fp16": { "enabled": true, "loss_scale": 0, "initial_scale_power": 16, "fp16_opt_level": "O2" ...
},"zero_optimization": {"stage":3,"offload_optimizer": {"device":"cpu","pin_memory":true},"overlap_comm":true,"contiguous_gradients":true,"sub_group_size":1e9,"reduce_bucket_size":"auto","stage3_prefetch_bucket_size":"auto","stage3_param_persistence_threshold":"auto","stage3_max...
开启Zero优化 要为DeepSpeed模型启用ZeRO优化,我们只需要将zero_optimization键添加到DeepSpeed JSON配置中。有关zero_optimization键的配置的完整描述,请参见此处(https://www.deepspeed.ai/docs/config-json/#zero-optimizations-for-fp16-training)。 训练一个1.5B参数的GPT2模型 我们通过展示ZeROStage 1的优点来演示...