wehub-resource-sync
86 lines
2.1 KiB
YAML
86 lines
2.1 KiB
YAML
# Distributed training runtime.
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infra:
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sequence_parallel_size: 4
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sharding_strategy: hybrid_full
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mixed_precision: true
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gradient_checkpointing: true
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vae_halo_latents: 28
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generator_fsdp_wrap_strategy: size
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text_encoder_fsdp_wrap_strategy: size
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# Passed directly to WanDiffusionWrapper(**model_kwargs).
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model_kwargs:
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model_name: Wan2.2-TI2V-5B
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timestep_shift: 5.0
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num_frame_per_block: 8
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local_attn_size: -1
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# AR diffusion objective.
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algorithm:
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trainer: diffusion
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causal: true
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teacher_forcing: true
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num_train_timestep: 1000
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denoising_loss_type: flow
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training:
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lr: 1.0e-05
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weight_decay: 0.0
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beta1: 0.0
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beta2: 0.999
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batch_size: 1
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gradient_accumulation_steps: 1
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ema_weight: 0.99
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ema_start_step: 100
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log_iters: 1
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max_checkpoints: 20
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max_iters: 600
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gc_interval: 100
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error_recycling:
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enabled: true
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num_buckets: 50
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buffer_size_per_bucket: 500
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buffer_warmup_iter: 50
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context_inject_prob: 0.9
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latent_inject_prob: 0.9
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noise_inject_prob: 0.01
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clean_prob: 0.2
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clean_buffer_update_prob: 0.1
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modulate_factor: 0.3
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start_step: 0
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replacement_strategy: random
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data:
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data_path: /path/to/longlive2/train_dataset
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eval_data_path: /path/to/longlive2/eval_prompts
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image_or_video_shape:
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- 1
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- 96
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- 48
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- 44
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- 80
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load_raw_video: true
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# Generation settings used by training-time evaluation.
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inference:
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sampling_steps: 50
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sink_size: 0
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multi_shot_sink: true
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multi_shot_rope_offset: 8
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guidance_scale: 3.0
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negative_prompt: '色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走'
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# Lightweight validation generation during AR training.
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evaluation:
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interval: 1
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num_frames: 16
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use_ema: true
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val_batch_size: 1
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save_latents_only: true
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logging:
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seed: 0
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wandb_key: null
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wandb_entity: null
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wandb_project: LongLive2-AR
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