Datasets:
File size: 2,659 Bytes
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audio:
chunk_size: 261632
dim_f: 4096
dim_t: 512
hop_length: 512
n_fft: 8192
num_channels: 2
sample_rate: 44100
min_mean_abs: 0.001
model:
encoder_name: tu-maxvit_large_tf_512 # look here for possibilities: https://github.com/qubvel/segmentation_models.pytorch#encoders-
decoder_type: unet # unet, fpn
act: gelu
num_channels: 128
num_subbands: 8
training:
batch_size: 7
gradient_accumulation_steps: 1
grad_clip: 0
instruments:
- vocals
- bass
- drums
- other
lr: 5.0e-05
patience: 2
reduce_factor: 0.95
target_instrument: null
num_epochs: 1000
num_steps: 2000
q: 0.95
coarse_loss_clip: true
ema_momentum: 0.999
optimizer: adamw
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
# apply mp3 compression to mixture only (emulate downloading mp3 from internet)
mp3_compression_on_mixture: 0.01
mp3_compression_on_mixture_bitrate_min: 32
mp3_compression_on_mixture_bitrate_max: 320
mp3_compression_on_mixture_backend: "lameenc"
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: 0.01
mp3_compression_min_bitrate: 32
mp3_compression_max_bitrate: 320
mp3_compression_backend: "lameenc"
vocals:
pitch_shift: 0.1
pitch_shift_min_semitones: -5
pitch_shift_max_semitones: 5
seven_band_parametric_eq: 0.25
seven_band_parametric_eq_min_gain_db: -9
seven_band_parametric_eq_max_gain_db: 9
tanh_distortion: 0.1
tanh_distortion_min: 0.1
tanh_distortion_max: 0.7
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: 0.01
time_stretch_min_rate: 0.8
time_stretch_max_rate: 1.25
inference:
batch_size: 1
dim_t: 512
num_overlap: 4 |