train_args_path:为Step2中需要配置的train_args路径 相关训练参数在train_args文件夹下对应的文件中。一般就是用dpo/dpo_config.py即可 均是采用dataclass格式配置参数,直接在default中修改即可,即不需要直接命令行传输参数了。 在这里修改max_len和max_prompt_length参数,其他需要设置的是是否选择deepspeed模式训练等...
do_train and not training_args.overwrite_output_dir: if os.path.isdir(training_args.output_dir) and not training_args.overwrite_output_dir: last_checkpoint = get_last_checkpoint(training_args.output_dir) if last_checkpoint is None and len(os.listdir(training_args.output_dir)) > 0: raise ...
CR_walker: 由train_redial,evaluation.py, args.option="test"开始到graph_walker 设置和调用。 我们先看prepare_data defprepare_data(self,mention_history,intent,node_candidate1,node_candidate2,label_1,label_2,device,sample=False,dataset="redial"):movie_cand=[0for_inrange(6924)]all_intent=["chat...
mindone examples animatediff args_train.py onmaster User selector All users DatepickerAll time Commit History Commits on Mar 22, 2024 Add min-snr weighting to improve AD training && Support any-shape infer (#398) SamitHuangcommittedMar 22, 2024 · 3 / 3 Verified 0b1bb8a Commits on Mar...
train_split=args.dataset_split, ) if args.iter is None: prompts_data = prompts_data.select(range(min(args.max_samples, len(prompts_data))) Expand Down Expand Up @@ -225,6 +227,7 @@ def batch_rm_inference(args): args.seed, return_eval=False, max_count=args.max_samples, train_spl...
torchcompile, mode=args.torchcompile_mode) elif args.aot_autograd: assert has_functorch, "functorch is needed for --aot-autograd" model = memory_efficient_fusion(model) 4 changes: 3 additions & 1 deletion 4 train.py Original file line numberDiff line numberDiff line change @@ -161,6 ...
以下是所有pod的运行情况截图: 以下是pod的报错信息以及pod内部mysql容器的报错信息 基本上所有无法正常运行的pod都是上述报错,也就是无法启动mysql容器。