Upload VideoX-Fun/gen_ref_videos.sh
Browse files- VideoX-Fun/gen_ref_videos.sh +53 -0
VideoX-Fun/gen_ref_videos.sh
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#!/bin/bash
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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..."
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# 1. 在这里预先定义你的参数数组 (a_i)
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# 数组元素的数量应该与你的任务数量(8)相匹配。
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# 参数可以是任何字符串，比如文件名、配置名、数值等。
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save_folder='data/ref_videos'
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sampler_name='Flow'
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prompt_list_path='/nfs/ywang29/Reward_finetuning/VideoX-Fun/VBench/prompts/all_dimension.txt'
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num_inference_steps=50
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# enable_teacache=False
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# params=(
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# "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct14_4/checkpoint-500/transformer/diffusion_pytorch_model.safetensors"
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# "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct14_7/checkpoint-1000/transformer/diffusion_pytorch_model.safetensors"
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# "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct14_5/checkpoint-500/transformer/diffusion_pytorch_model.safetensors"
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# "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct14_6/checkpoint-500/transformer/diffusion_pytorch_model.safetensors"
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# "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct14_6/checkpoint-1000/transformer/diffusion_pytorch_model.safetensors"
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# "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct14_6/checkpoint-2000/transformer/diffusion_pytorch_model.safetensors"
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# "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct14_7/checkpoint-500/transformer/diffusion_pytorch_model.safetensors"
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# "--transformer_path /nfs/ywang29/Reward_finetuning/VideoX-Fun/output_full/output_Oct14_7/checkpoint-2000/transformer/diffusion_pytorch_model.safetensors"
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# )
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params=(
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"--prompt_list_path ref_video_prompt_list_part_0.txt"
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"--prompt_list_path ref_video_prompt_list_part_1.txt"
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"--prompt_list_path ref_video_prompt_list_part_2.txt"
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"--prompt_list_path ref_video_prompt_list_part_3.txt"
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"--prompt_list_path ref_video_prompt_list_part_4.txt"
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"--prompt_list_path ref_video_prompt_list_part_5.txt"
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"--prompt_list_path ref_video_prompt_list_part_6.txt"
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"--prompt_list_path ref_video_prompt_list_part_7.txt"
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)
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# 2. 修改循环以遍历数组的索引
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# ${!params[@]} 会获取数组 params 的所有索引 (0 1 2 3 4 5 6 7)
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for i in "${!params[@]}"
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do
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# 从数组中获取当前索引对应的参数值
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current_param="${params[$i]}"
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# CUDA_VISIBLE_DEVICES=$i 告诉程序只能“看见”并使用第 i 张 GPU
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# python X.py --p "$current_param" 将当前参数传递给脚本
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# & 让命令在后台运行
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echo "启动任务 $i (GPU $i)，参数为: $current_param"
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CUDA_VISIBLE_DEVICES=$i python ./examples/wan2.1/predict_t2v_14B_vqref.py --prompt_list_path $prompt_list_path --num_inference_steps $num_inference_steps --save_folder $save_folder --sampler_name $sampler_name $current_param &
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done
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# 'wait' 命令会等待所有后台任务都执行完毕
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echo "所有任务已启动。等待它们全部完成..."
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wait
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echo "所有任务已完成。"
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