42 lines
1.4 KiB
Bash
42 lines
1.4 KiB
Bash
export MODEL_NAME="models/Diffusion_Transformer/EasyAnimateV5.1-12b-zh-Control"
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export DATASET_NAME="datasets/internal_datasets/"
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export DATASET_META_NAME="datasets/internal_datasets/metadata.json"
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export NCCL_IB_DISABLE=1
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export NCCL_P2P_DISABLE=1
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NCCL_DEBUG=INFO
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# When train model with multi machines, use "--config_file accelerate.yaml" instead of "--mixed_precision='bf16'".
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accelerate launch --mixed_precision="bf16" scripts/train_control.py \
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--pretrained_model_name_or_path=$MODEL_NAME \
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--train_data_dir=$DATASET_NAME \
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--train_data_meta=$DATASET_META_NAME \
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--config_path "config/easyanimate_video_v5.1_magvit_qwen.yaml" \
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--image_sample_size=1024 \
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--video_sample_size=256 \
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--token_sample_size=512 \
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--video_sample_stride=3 \
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--video_sample_n_frames=49 \
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--train_batch_size=1 \
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--video_repeat=1 \
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--gradient_accumulation_steps=1 \
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--dataloader_num_workers=8 \
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--num_train_epochs=100 \
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--checkpointing_steps=100 \
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--learning_rate=2e-05 \
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--lr_scheduler="constant_with_warmup" \
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--lr_warmup_steps=100 \
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--seed=42 \
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--output_dir="output_dir" \
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--gradient_checkpointing \
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--mixed_precision="bf16" \
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--adam_weight_decay=5e-3 \
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--adam_epsilon=1e-10 \
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--vae_mini_batch=1 \
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--max_grad_norm=0.05 \
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--random_hw_adapt \
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--training_with_video_token_length \
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--loss_type="flow" \
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--enable_bucket \
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--uniform_sampling \
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--train_mode="control_ref" \
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--trainable_modules "." |