File size: 3,966 Bytes
d6162c5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | #!/bin/bash
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_vbench2_all_aug'
sampler_name='Flow'
num_generated_videos=-1
prompt_list_path='/nfs/ywang29/Reward_finetuning/VideoX-Fun/VBench/VBench-2.0/prompts/prompt_aug/VBench2_full_text_aug.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/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=(
"--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct18_2/checkpoint-3000/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-3000/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-3000/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}/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 --save_folder ${save_folder}"
)
# 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"
done
|