steps_per_print:配置中取值10; prescale_gradients:配置中配置为false; gradient_clipping:配置中取值为1.0; zero_config:zero_optimization配置参数; zero_optimization_stage:zero_optimization配置参数中"stage"参数; zero_enabled:zero_optimization_stage是否大于0; …… activation_checkpointing_config:初始化DeepSpeed...
#每个GPU的bs"steps_per_print":1000,#打印间隔"prescale_gradients":false,"optimizer":{#优化器相关...
针对模型状态的存储优化(去除冗余),ZeRO使用的方法是分片,即每张卡只存 1/N的模型状态量,这样系统内只维护一份模型状态。 ZeRO 具有三个主要的优化阶段(ZeRO-1,ZeRO-2,ZeRO-3),它们对应于优化器状态(optimizer states)、梯度(gradients)和参数(parameters)的分片。累积启用时: 优化器状态分区 (P_{os}) – ...
worker-0: optimizer_params ... {'lr': 0.001, 'betas': [0.8, 0.999], 'eps': 1e-08, 'weight_decay': 3e-07} worker-0: prescale_gradients ... False worker-0: scheduler_name ... WarmupLR worker-0: scheduler_params ... {'warmup_min_lr': 0, 'warmup_max_lr': 0.001, 'warm...
"prescale_gradients":False,#是否在梯度累计之前就进行梯度缩放,通常用于防止梯度下溢。 "wall_clock_breakdown":False,#是否进行每步训练时间的详细分析。 "hybrid_engine":{ "enabled":enable_hybrid_engine, "max_out_tokens":max_out_tokens, "inference_tp_size":inference_tp_size, "release_inference_cache...
[2024-01-18 10:49:19,677] [INFO] [config.py:988:print] prescale_gradients ... False [2024-01-18 10:49:19,677] [INFO] [config.py:988:print] scheduler_name ... None [2024-01-18 10:49:19,677] [INFO] [config.py:988:print] scheduler_params ... None [2024-01-18 10:49:19...
{ "warmup_min_lr": 0, "warmup_max_lr": 0.001, "warmup_num_steps": 1000, }, }, "gradient_clipping": 1.0, "prescale_gradients": False, "bf16": {"enabled": args.dtype == "bf16"}, "fp16": { "enabled": args.dtype == "fp16", "fp16_master_weights_and_grads": False, ...
而其在今年推出 DeepSpeed-Chat，通过其 DeepSpeed-RLHF 系统在大规模训练中显著提升训练效率，能够适配...
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