model:
  audio_encoder: # input (1, 80, 52)
    in_channels: 1
    block_out_channels: [32, 64, 128, 256, 512, 1024, 2048]
    downsample_factors: [[2, 1], 2, 2, 1, 2, 2, [2, 3]]
    attn_blocks: [0, 0, 0, 0, 0, 0, 0]
    dropout: 0.0
  visual_encoder: # input (48, 128, 256)
    in_channels: 48
    block_out_channels: [64, 128, 256, 256, 512, 1024, 2048, 2048]
    downsample_factors: [[1, 2], 2, 2, 2, 2, 2, 2, 2]
    attn_blocks: [0, 0, 0, 0, 0, 0, 0, 0]
    dropout: 0.0

ckpt:
  resume_ckpt_path: ""
  inference_ckpt_path: ""
  save_ckpt_steps: 2500

data:
  train_output_dir: debug/syncnet
  num_val_samples: 2048
  batch_size: 256 # 256
  gradient_accumulation_steps: 1
  num_workers: 12 # 12
  latent_space: false
  num_frames: 16
  resolution: 256
  train_fileslist: /mnt/bn/maliva-gen-ai-v2/chunyu.li/fileslist/data_v10_core.txt
  train_data_dir: ""
  val_fileslist: ""
  val_data_dir: /mnt/bn/maliva-gen-ai-v2/chunyu.li/VoxCeleb2/high_visual_quality/val
  audio_mel_cache_dir: /mnt/bn/maliva-gen-ai-v2/chunyu.li/audio_cache/mel
  lower_half: true
  audio_sample_rate: 16000
  video_fps: 25

optimizer:
  lr: 1e-5
  max_grad_norm: 1.0

run:
  max_train_steps: 10000000
  validation_steps: 2500
  mixed_precision_training: true
  seed: 42
