48 lines
1.8 KiB
Bash
48 lines
1.8 KiB
Bash
export VIDEOX_OFFLOAD_VACE_LATENTS=True
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export MODEL_NAME="models/Diffusion_Transformer/MiniMax-H3"
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export DATASET_NAME="datasets/X-Fun-Videos-Controls-Demo/"
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export DATASET_META_NAME="datasets/X-Fun-Videos-Controls-Demo/metadata_add_width_height_add_wav.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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accelerate launch --mixed_precision="bf16" \
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--use_fsdp --fsdp_auto_wrap_policy TRANSFORMER_BASED_WRAP \
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--fsdp_transformer_layer_cls_to_wrap BaseMiniMaxH3TransformerBlock,MiniMaxH3ControlTransformerBlock \
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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/minimax_h3_fun/train_control.py \
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--config_path="config/minimax_h3/minimax_h3_control.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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--video_sample_size=960 \
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--token_sample_size=960 \
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--video_sample_stride=1 \
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--video_sample_n_frames=311 \
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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=50 \
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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_minimax_h3_control_inpaint" \
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--gradient_checkpointing \
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--gradient_checkpointing_save_on_cpu \
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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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--enable_bucket \
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--enable_inpaint \
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--low_vram \
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--uniform_sampling \
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--trainable_modules "control" \
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--resume_from_checkpoint=latest
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