52 lines
2.0 KiB
Bash
52 lines
2.0 KiB
Bash
export MODEL_NAME="models/Diffusion_Transformer/Wan2.1-T2V-1.3B/"
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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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# NCCL_IB_DISABLE=1 and NCCL_P2P_DISABLE=1 are used in multi nodes without RDMA.
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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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# Causal-Forcing Stage 1: Autoregressive Diffusion Training (teacher forcing).
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# - num_frame_per_block=3 -> chunkwise; set to 1 for the framewise variant.
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# - shift=5.0 mirrors the Causal-Forcing default scheduler shift.
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accelerate launch --mixed_precision="bf16" --use_fsdp \
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--fsdp_auto_wrap_policy TRANSFORMER_BASED_WRAP \
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--fsdp_transformer_layer_cls_to_wrap=CasualWanAttentionBlock \
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--fsdp_sharding_strategy "FULL_SHARD" --fsdp_state_dict_type=SHARDED_STATE_DICT \
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--fsdp_backward_prefetch "BACKWARD_PRE" --fsdp_cpu_ram_efficient_loading False \
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scripts/wan2.1_causal_forcing/train_ar_diffusion.py \
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--config_path="config/wan2.1/wan_civitai.yaml" \
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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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--image_sample_size=640 \
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--video_sample_size=640 \
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--token_sample_size=640 \
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--fix_sample_size 480 832 \
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--video_sample_stride=2 \
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--video_sample_n_frames=81 \
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--train_batch_size=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=200 \
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--learning_rate=2e-06 \
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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_wan2.1_causal_forcing_ar_diffusion" \
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--gradient_checkpointing \
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--mixed_precision="bf16" \
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--adam_weight_decay=3e-2 \
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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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--enable_bucket \
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--num_frame_per_block=3 \
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--train_sampling_steps=1000 \
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--shift=5.0 \
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--use_timestep_weight \
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--trainable_modules "."
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