audio: | |
chunk_size: 264600 | |
num_channels: 2 | |
sample_rate: 44100 | |
min_mean_abs: 0.000 | |
model: | |
dims: [4, 32, 64, 128] | |
bandsplit_ratios: [.175, .392, .433] | |
downsample_strides: [1, 4, 16] | |
n_conv_modules: [3, 2, 1] | |
n_rnn_layers: 6 | |
rnn_hidden_dim: 128 | |
n_sources: 2 | |
n_fft: 4096 | |
hop_length: 1024 | |
win_length: 4096 | |
stft_normalized: false | |
use_mamba: false | |
d_state: 16 | |
d_conv: 4 | |
d_expand: 2 | |
training: | |
batch_size: 10 | |
gradient_accumulation_steps: 2 | |
grad_clip: 0 | |
instruments: | |
- vocals | |
- other | |
lr: 5.0e-04 | |
patience: 2 | |
reduce_factor: 0.95 | |
target_instrument: null | |
num_epochs: 1000 | |
num_steps: 1000 | |
q: 0.95 | |
coarse_loss_clip: true | |
ema_momentum: 0.999 | |
optimizer: adam | |
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: 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 | |
inference: | |
batch_size: 8 | |
dim_t: 256 | |
num_overlap: 4 | |