| echo "正在启动 8 个并行的独立任务，并为每个任务分配不同参数..." | |
| # 1. 在这里预先定义你的参数数组 (a_i) | |
| # 数组元素的数量应该与你的任务数量(8)相匹配。 | |
| # 参数可以是任何字符串，比如文件名、配置名、数值等。 | |
| save_folder='validation_samples/samples_vbench_all_longer' | |
| sampler_name='Flow' | |
| num_generated_videos=-1 | |
| prompt_list_path='/nfs/ywang29/Reward_finetuning/VideoX-Fun/VBench/prompts/augmented_prompts/gpt_enhanced_prompts/all_prompts_longer.txt' | |
| # enable_teacache=False | |
| # params=( | |
| # "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct14_4/checkpoint-500/transformer/diffusion_pytorch_model.safetensors" | |
| # "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct14_7/checkpoint-1000/transformer/diffusion_pytorch_model.safetensors" | |
| # "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct14_5/checkpoint-500/transformer/diffusion_pytorch_model.safetensors" | |
| # "--transformer_path /nfs/ywang29/ckpts/Wan2.1-1.3B-ft/ckpts_full_chunk3/output_Oct14_6/checkpoint-500/transformer/diffusion_pytorch_model.safetensors" | |
| # "--transformer_path /nfs/ywang29/ckpts/Wan2.1-1.3B-ft/ckpts_full_chunk3/output_Oct14_6/checkpoint-1000/transformer/diffusion_pytorch_model.safetensors" | |
| # "--transformer_path /nfs/ywang29/ckpts/Wan2.1-1.3B-ft/ckpts_full_chunk3/output_Oct14_6/checkpoint-2000/transformer/diffusion_pytorch_model.safetensors" | |
| # "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct14_7/checkpoint-500/transformer/diffusion_pytorch_model.safetensors" | |
| # "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct14_7/checkpoint-2000/transformer/diffusion_pytorch_model.safetensors" | |
| # ) | |
| params=( | |
| " --seed -1 --save_folder ${save_folder}/r1" | |
| " --seed -1 --save_folder ${save_folder}/r2" | |
| " --seed -1 --save_folder ${save_folder}/r3" | |
| "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct18_2/checkpoint-2000/transformer/diffusion_pytorch_model.safetensors --seed -1 --save_folder ${save_folder}/r1" | |
| "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct18_2/checkpoint-2000/transformer/diffusion_pytorch_model.safetensors --seed -1 --save_folder ${save_folder}/r2" | |
| "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct18_2/checkpoint-2000/transformer/diffusion_pytorch_model.safetensors --seed -1 --save_folder ${save_folder}/r3" | |
| "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct18_2/checkpoint-2000/transformer/diffusion_pytorch_model.safetensors --seed -1 --save_folder ${save_folder}/r4" | |
| "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct18_2/checkpoint-2000/transformer/diffusion_pytorch_model.safetensors --seed -1 --save_folder ${save_folder}/r5" | |
| ) | |
| # 2. 修改循环以遍历数组的索引 | |
| # ${!params[@]} 会获取数组 params 的所有索引 (0 1 2 3 4 5 6 7) | |
| for i in "${!params[@]}" | |
| do | |
| # 从数组中获取当前索引对应的参数值 | |
| current_param="${params[$i]}" | |
| # CUDA_VISIBLE_DEVICES=$i 告诉程序只能“看见”并使用第 i 张 GPU | |
| # python X.py --p "$current_param" 将当前参数传递给脚本 | |
| # & 让命令在后台运行 | |
| echo "启动任务 $i (GPU $i)，参数为: $current_param" | |
| CUDA_VISIBLE_DEVICES=$i python ./examples/wan2.1/predict_t2v_val2.py --prompt_list_path $prompt_list_path --num_generated_videos $num_generated_videos --sampler_name $sampler_name $current_param & | |
| done | |
| # 'wait' 命令会等待所有后台任务都执行完毕 | |
| echo "所有任务已启动。等待它们全部完成..." | |
| wait | |
| echo "所有任务已完成。" |