BS-Rofo-SW-Fixed.yaml

audio:
  chunk_size: 588800 #882000
  dim_f: 1024
  dim_t: 801 # don't work (use in model)
  hop_length: 441 # don't work (use in model)
  n_fft: 2048
  num_channels: 2
  sample_rate: 44100
  min_mean_abs: 0.000

model:
  dim: 256
  depth: 12
  stereo: true
  num_stems: 6
  time_transformer_depth: 1
  freq_transformer_depth: 1
  linear_transformer_depth: 0
  freqs_per_bands: !!python/tuple
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 2
    - 4
    - 4
    - 4
    - 4
    - 4
    - 4
    - 4
    - 4
    - 4
    - 4
    - 4
    - 4
    - 12
    - 12
    - 12
    - 12
    - 12
    - 12
    - 12
    - 12
    - 24
    - 24
    - 24
    - 24
    - 24
    - 24
    - 24
    - 24
    - 48
    - 48
    - 48
    - 48
    - 48
    - 48
    - 48
    - 48
    - 128
    - 129
  dim_head: 64
  heads: 8
  attn_dropout: 0.1
  ff_dropout: 0.1
  flash_attn: true
  dim_freqs_in: 1025
  stft_n_fft: 2048
  stft_hop_length: 512
  stft_win_length: 2048
  stft_normalized: false
  mask_estimator_depth: 2
  multi_stft_resolution_loss_weight: 1.0
  multi_stft_resolutions_window_sizes: !!python/tuple
  - 4096
  - 2048
  - 1024
  - 512
  - 256
  multi_stft_hop_size: 147
  multi_stft_normalized: False
  mlp_expansion_factor: 4
  use_torch_checkpoint: False # it allows to greatly reduce GPU memory consumption during training (not fully tested)
  skip_connection: False # Enable skip connection between transformer blocks - can solve problem with gradients and probably faster training

training:
  batch_size: 2
  gradient_accumulation_steps: 1
  grad_clip: 0
  instruments: ['bass', 'drums', 'other', 'vocals', 'guitar', 'piano']
  patience: 3
  reduce_factor: 0.95
  target_instrument: null
  num_epochs: 1000
  num_steps: 1000
  augmentation: false # enable augmentations by audiomentations and pedalboard
  augmentation_type: simple1
  use_mp3_compress: false # Deprecated
  augmentation_mix: true # Mix several stems of the same type with some probability
  augmentation_loudness: true # randomly change loudness of each stem
  augmentation_loudness_type: 1 # Type 1 or 2
  augmentation_loudness_min: 0.5
  augmentation_loudness_max: 1.5
  q: 0.95
  coarse_loss_clip: true
  ema_momentum: 0.999
  # optimizer: prodigy
  optimizer: adam
  # lr: 1.0
  lr: 1.0e-5
  other_fix: false # it's needed for checking on multisong dataset if other is actually instrumental
  use_amp: true # enable or disable usage of mixed precision (float16) - usually it must be true

augmentations:
  enable: true # enable or disable all augmentations (to fast disable if needed)
  loudness: true # randomly change loudness of each stem on the range (loudness_min; loudness_max)
  loudness_min: 0.5
  loudness_max: 1.5
  mixup: true # mix several stems of same type with some probability (only works for dataset types: 1, 2, 3)
  mixup_probs: !!python/tuple # 2 additional stems of the same type (1st with prob 0.2, 2nd with prob 0.02)
    - 0.2
    - 0.02
  mixup_loudness_min: 0.5
  mixup_loudness_max: 1.5

  all:
    channel_shuffle: 0.5 # Set 0 or lower to disable
    random_inverse: 0.1 # inverse track (better lower probability)
    random_polarity: 0.5 # polarity change (multiply waveform to -1)

  vocals:
      pitch_shift: 0.1
      pitch_shift_min_semitones: -5
      pitch_shift_max_semitones: 5
      seven_band_parametric_eq: 0.1
      seven_band_parametric_eq_min_gain_db: -9
      seven_band_parametric_eq_max_gain_db: 9
      tanh_distortion: 0.1
      tanh_distortion_min: 0.1
      tanh_distortion_max: 0.7
  bass:
    pitch_shift: 0.1
    pitch_shift_min_semitones: -2
    pitch_shift_max_semitones: 2
    seven_band_parametric_eq: 0.1
    seven_band_parametric_eq_min_gain_db: -3
    seven_band_parametric_eq_max_gain_db: 6
    tanh_distortion: 0.1
    tanh_distortion_min: 0.1
    tanh_distortion_max: 0.5
  drums:
    pitch_shift: 0.1
    pitch_shift_min_semitones: -5
    pitch_shift_max_semitones: 5
    seven_band_parametric_eq: 0.1
    seven_band_parametric_eq_min_gain_db: -9
    seven_band_parametric_eq_max_gain_db: 9
    tanh_distortion: 0.1
    tanh_distortion_min: 0.1
    tanh_distortion_max: 0.6
  other:
    pitch_shift: 0.1
    pitch_shift_min_semitones: -4
    pitch_shift_max_semitones: 4
    gaussian_noise: 0.1
    gaussian_noise_min_amplitude: 0.001
    gaussian_noise_max_amplitude: 0.015
    time_stretch: 0.1
    time_stretch_min_rate: 0.8
    time_stretch_max_rate: 1.25


inference:
  batch_size: 1
  dim_t: 1101
  num_overlap: 2
  normalize: false