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export MODEL_NAME="models/Diffusion_Transformer/Wan2.2-Fun-A14B-InP"
export DATASET_NAME="datasets/internal_datasets/"
export DATASET_META_NAME="datasets/internal_datasets/metadata.json"
# NCCL_IB_DISABLE=1 and NCCL_P2P_DISABLE=1 are used in multi nodes without RDMA.
# export NCCL_IB_DISABLE=1
# export NCCL_P2P_DISABLE=1
NCCL_DEBUG=INFO
accelerate launch --mixed_precision="bf16" scripts/wan2.2_fun/train.py \
--config_path="config/wan2.2/wan_civitai_i2v.yaml" \
--pretrained_model_name_or_path=$MODEL_NAME \
--train_data_dir=$DATASET_NAME \
--train_data_meta=$DATASET_META_NAME \
--image_sample_size=640 \
--video_sample_size=640 \
--token_sample_size=640 \
--video_sample_stride=2 \
--video_sample_n_frames=81 \
--train_batch_size=1 \
--video_repeat=1 \
--gradient_accumulation_steps=1 \
--dataloader_num_workers=8 \
--num_train_epochs=100 \
--checkpointing_steps=50 \
--learning_rate=2e-05 \
--lr_scheduler="constant_with_warmup" \
--lr_warmup_steps=100 \
--seed=42 \
--output_dir="output_dir" \
--gradient_checkpointing \
--mixed_precision="bf16" \
--adam_weight_decay=3e-2 \
--adam_epsilon=1e-10 \
--vae_mini_batch=1 \
--max_grad_norm=0.05 \
--random_hw_adapt \
--training_with_video_token_length \
--enable_bucket \
--uniform_sampling \
--low_vram \
--boundary_type="low" \
--train_mode="inpaint" \
--trainable_modules "." |