File size: 4,075 Bytes
aef0324 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 |
audio:
chunk_size: 352800
dim_f: 1024
dim_t: 801
hop_length: 441
n_fft: 2048
num_channels: 2
sample_rate: 44100
min_mean_abs: 0.000
model:
dim: 512
depth: 16
stereo: true
num_stems: 1
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: 441
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
training:
batch_size: 1
gradient_accumulation_steps: 1
grad_clip: 0
instruments:
- vocals
- other
lr: 2.0e-07
patience: 2
reduce_factor: 0.95
target_instrument: vocals
num_epochs: 1000
num_steps: 5000
q: 0.95
coarse_loss_clip: true
ema_momentum: 0.999
optimizer: adamw8bit
other_fix: true # 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: false # 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: 0.25
mixup_loudness_max: 1.75
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)
mp3_compression: 0.05
mp3_compression_min_bitrate: 32
mp3_compression_max_bitrate: 320
mp3_compression_backend: "lameenc"
# pedalboard resample block
pedalboard_resample: 0.001
pedalboard_resample_target_sample_rate_min: 4000
pedalboard_resample_target_sample_rate_max: 44100
# pedalboard mp3 compressor block
pedalboard_mp3_compressor: 0.005
pedalboard_mp3_compressor_pedalboard_mp3_compressor_min: 0
pedalboard_mp3_compressor_pedalboard_mp3_compressor_max: 9.999
vocals:
pitch_shift: 0.25
pitch_shift_min_semitones: -7
pitch_shift_max_semitones: 7
seven_band_parametric_eq: 0.25
seven_band_parametric_eq_min_gain_db: -9
seven_band_parametric_eq_max_gain_db: 9
tanh_distortion: 0.01
tanh_distortion_min: 0.1
tanh_distortion_max: 0.7
pedalboard_reverb: 0.01
pedalboard_reverb_room_size_min: 0.1
pedalboard_reverb_room_size_max: 0.9
pedalboard_reverb_damping_min: 0.1
pedalboard_reverb_damping_max: 0.9
pedalboard_reverb_wet_level_min: 0.1
pedalboard_reverb_wet_level_max: 0.9
pedalboard_reverb_dry_level_min: 0.1
pedalboard_reverb_dry_level_max: 0.9
pedalboard_reverb_width_min: 0.9
pedalboard_reverb_width_max: 1.0
inference:
batch_size: 2
dim_t: 1101
num_overlap: 2 |