accelerate launch --multi_gpu --gpu_ids '0,1,2,3,4,5,6,7' --main_process_port 25011 --num_processes 8 \
    train/extract_features.py \
    --csv_path /mnt/VideoGen/dataset/OpenVid1M/video_reorg/OpenVid1M_reorganized.csv \
    --output_dir /mnt/VideoGen/dataset/OpenVid1M/extracted_features_17_128_128 \
    --text_encoder_architecture umt5-xxl \
    --video_tokenizer_model_id Cosmos-0.1-Tokenizer-DV4x8x8 \
    --num_frames 17 \
    --video_height 128 \
    --video_width 128 \
    --batch_size 64 \
    --num_workers 8 \
    --extract_text
    # --extract_video
    
    
# python train/extract_empty_embeds.py \
#     --text_encoder_architecture umt5-base \
#     --output_path /path/to/empty_embeds.pt \
#     --dtype float16


# python train/train_mei_video.py \
#     --use_precomputed_features \
#     --features_dir /path/to/extracted_features \
#     --text_encoder_architecture umt5-base \
#     --video_tokenizer_model_id Cosmos-1.0-Tokenizer-DV8x16x16 \
#     --num_frames 16 \
#     --video_height 480 \
#     --video_width 848 \
#     --train_batch_size 8 \
#     --learning_rate 3e-4 \
#     --max_train_steps 10000 \
#     --output_dir ./output \
#     --mixed_precision bf16


# python train/check_codebook_range.py \
#     --csv_path /mnt/VideoGen/dataset/OpenVid1M/video_reorg/OpenVid1M_reorganized.csv \
#     --video_tokenizer_model_id Cosmos-0.1-Tokenizer-DV4x8x8 \
#     --num_frames 16 \
#     --video_height 480 \
#     --video_width 848 \
#     --check_interval 10 \
#     --max_samples 1000  # 可选：限制检查的样本数