86 lines
4.0 KiB
Bash
86 lines
4.0 KiB
Bash
export MODEL_NAME="models/Diffusion_Transformer/Wan2.1-T2V-1.3B/"
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export REAL_SCORE_MODEL_NAME="models/Diffusion_Transformer/Wan2.1-T2V-14B"
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# One-Forcing needs REAL videos to build the adversarial critic's clean_latents, so the dataset
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# must be a video meta (type=video + file_path), NOT a prompt-only json. The official demo
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# dataset X-Fun-Videos-Demo ships captioned videos and is normalized by --enable_bucket
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# --random_hw_adapt --training_with_video_token_length.
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export DATASET_NAME="datasets/X-Fun-Videos-Demo/"
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export DATASET_META_NAME="datasets/X-Fun-Videos-Demo/metadata_add_width_height.json"
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# Warm-start generator: a distilled/ODE checkpoint that the DMD + adversarial critic then polish.
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# Default: the official One-Forcing ODE-initialized checkpoint, downloaded via
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# hf download JiaqiFeng/OneForcing checkpoints/framewise/causal_ode.pt --local-dir models/Diffusion_Transformer/One-Forcing
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# You can also point it at your own Causal-Forcing Stage-2 CCD checkpoint.
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export STAGE2_CKPT="models/Diffusion_Transformer/One-Forcing/checkpoints/framewise/causal_ode.pt"
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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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# One-Forcing = Causal-Forcing Stage-3 DMD + a shared noised-latent adversarial critic on fake_score.
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# - 1-step frame-wise generation: --denoising_step_indices_list 1000, --num_frame_per_block=1;
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# 21 latent frames from --video_sample_n_frames=81 @ 480x832.
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# - GAN critic: gan_g_weight/gan_d_weight=0.03, feature layers [21, 29], ffn 2048, heads 12,
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# non-relativistic, R1/R2 off. The head rides on fake_score and is training-only.
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# - GAN requires real videos, --gradient_accumulation_steps=1, no DeepSpeed, and --video_sample_stride=1
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# (stride=2 on 81-frame sources yields ~10 latent frames < score_num_frames=21 and aborts).
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# - guidance: local CFG is cond + scale*(cond - uncond), so --real_guidance_scale=6.0.
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# - optimizer/EMA/steps: lr=lr_critic=1e-5, betas (0.0, 0.999), weight_decay=0.01,
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# --use_ema --ema_decay=0.99, gen_update_interval=5, max_steps=200.
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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_one_forcing/train_one_forcing.py \
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--config_path="config/wan2.1/wan_civitai.yaml" \
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--pretrained_model_name_or_path=$MODEL_NAME \
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--real_score_pretrained_model_name_or_path=$REAL_SCORE_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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--ode_transformer_path=$STAGE2_CKPT \
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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=1 \
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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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--max_train_steps=200 \
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--checkpointing_steps=100 \
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--learning_rate=1.0e-05 \
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--learning_rate_critic=1.0e-05 \
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--lr_scheduler="constant" \
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--seed=42 \
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--output_dir="output_dir_wan2.1_one_forcing_framewise_1step" \
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--gradient_checkpointing \
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--mixed_precision="bf16" \
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--fsdp_reduce_fp32 \
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--adam_weight_decay=0.01 \
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--adam_beta1=0.0 \
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--adam_beta2=0.999 \
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--adam_epsilon=1e-08 \
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--vae_mini_batch=1 \
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--max_grad_norm=10.0 \
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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=1 \
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--use_kv_cache_training \
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--use_ema \
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--ema_decay=0.99 \
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--denoising_step_indices_list 1000 \
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--real_guidance_scale=6.0 \
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--score_timestep_clamp \
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--fake_guidance_scale=0.0 \
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--gen_update_interval=5 \
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--gan_g_weight=0.03 \
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--gan_d_weight=0.03 \
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--gan_feature_layers 21 29 \
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--gan_block_ffn_dim=2048 \
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--gan_block_num_heads=12 \
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--resume_from_checkpoint="latest" \
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--trainable_modules "."
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