Delete configs

configs/config_dnr_bandit_bsrnn_multi_mus64.yaml

@@ -1,78 +0,0 @@
-name: "MultiMaskMultiSourceBandSplitRNN"
-audio:
-  chunk_size: 264600
-  num_channels: 2
-  sample_rate: 44100
-  min_mean_abs: 0.001
-
-model:
-  in_channel: 1
-  stems: ['speech', 'music', 'effects']
-  band_specs: "musical"
-  n_bands: 64
-  fs: 44100
-  require_no_overlap: false
-  require_no_gap: true
-  normalize_channel_independently: false
-  treat_channel_as_feature: true
-  n_sqm_modules: 8
-  emb_dim: 128
-  rnn_dim: 256
-  bidirectional: true
-  rnn_type: "GRU"
-  mlp_dim: 512
-  hidden_activation: "Tanh"
-  hidden_activation_kwargs: null
-  complex_mask: true
-  n_fft: 2048
-  win_length: 2048
-  hop_length: 512
-  window_fn: "hann_window"
-  wkwargs: null
-  power: null
-  center: true
-  normalized: true
-  pad_mode: "constant"
-  onesided: true
-
-training:
-  batch_size: 4
-  gradient_accumulation_steps: 4
-  grad_clip: 0
-  instruments:
-  - speech
-  - music
-  - effects
-  lr: 9.0e-05
-  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
-  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)
-
-inference:
-  batch_size: 1
-  dim_t: 256
-  num_overlap: 4

configs/config_htdemucs_6stems.yaml

@@ -1,127 +0,0 @@
-audio:
-  chunk_size: 485100 # samplerate * segment
-  min_mean_abs: 0.001
-  hop_length: 1024
-
-training:
-  batch_size: 8
-  gradient_accumulation_steps: 1
-  grad_clip: 0
-  segment: 11
-  shift: 1
-  samplerate: 44100
-  channels: 2
-  normalize: true
-  instruments: ['drums', 'bass', 'other', 'vocals', 'guitar', 'piano']
-  target_instrument: null
-  num_epochs: 1000
-  num_steps: 1000
-  optimizer: adam
-  lr: 9.0e-05
-  patience: 2
-  reduce_factor: 0.95
-  q: 0.95
-  coarse_loss_clip: true
-  ema_momentum: 0.999
-  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: [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)
-
-inference:
-  num_overlap: 4
-  batch_size: 8
-
-model: htdemucs
-
-htdemucs:  # see demucs/htdemucs.py for a detailed description
-  # Channels
-  channels: 48
-  channels_time:
-  growth: 2
-  # STFT
-  num_subbands: 1
-  nfft: 4096
-  wiener_iters: 0
-  end_iters: 0
-  wiener_residual: false
-  cac: true
-  # Main structure
-  depth: 4
-  rewrite: true
-  # Frequency Branch
-  multi_freqs: []
-  multi_freqs_depth: 3
-  freq_emb: 0.2
-  emb_scale: 10
-  emb_smooth: true
-  # Convolutions
-  kernel_size: 8
-  stride: 4
-  time_stride: 2
-  context: 1
-  context_enc: 0
-  # normalization
-  norm_starts: 4
-  norm_groups: 4
-  # DConv residual branch
-  dconv_mode: 3
-  dconv_depth: 2
-  dconv_comp: 8
-  dconv_init: 1e-3
-  # Before the Transformer
-  bottom_channels: 0
-  # CrossTransformer
-  # ------ Common to all
-  # Regular parameters
-  t_layers: 5
-  t_hidden_scale: 4.0
-  t_heads: 8
-  t_dropout: 0.0
-  t_layer_scale: True
-  t_gelu: True
-  # ------------- Positional Embedding
-  t_emb: sin
-  t_max_positions: 10000 # for the scaled embedding
-  t_max_period: 10000.0
-  t_weight_pos_embed: 1.0
-  t_cape_mean_normalize: True
-  t_cape_augment: True
-  t_cape_glob_loc_scale: [5000.0, 1.0, 1.4]
-  t_sin_random_shift: 0
-  # ------------- norm before a transformer encoder
-  t_norm_in: True
-  t_norm_in_group: False
-  # ------------- norm inside the encoder
-  t_group_norm: False
-  t_norm_first: True
-  t_norm_out: True
-  # ------------- optim
-  t_weight_decay: 0.0
-  t_lr:
-  # ------------- sparsity
-  t_sparse_self_attn: False
-  t_sparse_cross_attn: False
-  t_mask_type: diag
-  t_mask_random_seed: 42
-  t_sparse_attn_window: 400
-  t_global_window: 100
-  t_sparsity: 0.95
-  t_auto_sparsity: False
-  # Cross Encoder First (False)
-  t_cross_first: False
-  # Weight init
-  rescale: 0.1
-

configs/config_musdb18_bs_roformer.yaml

@@ -1,134 +0,0 @@
-audio:
-  chunk_size: 131584
-  dim_f: 1024
-  dim_t: 256
-  hop_length: 512
-  n_fft: 2048
-  num_channels: 2
-  sample_rate: 44100
-  min_mean_abs: 0.001
-
-model:
-  dim: 192
-  depth: 6
-  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: 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
-
-training:
-  batch_size: 10
-  gradient_accumulation_steps: 1
-  grad_clip: 0
-  instruments:
-  - vocals
-  - bass
-  - drums
-  - other
-  lr: 5.0e-05
-  patience: 2
-  reduce_factor: 0.95
-  target_instrument: vocals
-  num_epochs: 1000
-  num_steps: 1000
-  q: 0.95
-  coarse_loss_clip: true
-  ema_momentum: 0.999
-  optimizer: adam
-  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
-
-inference:
-  batch_size: 1
-  dim_t: 256
-  num_overlap: 4

configs/config_musdb18_demucs3_mmi.yaml

@@ -1,72 +0,0 @@
-audio:
-  chunk_size: 485100 # samplerate * segment
-  min_mean_abs: 0.000
-  hop_length: 1024
-
-training:
-  batch_size: 8
-  gradient_accumulation_steps: 1
-  grad_clip: 0
-  segment: 11
-  shift: 1
-  samplerate: 44100
-  channels: 2
-  normalize: true
-  instruments: ['drums', 'bass', 'other', 'vocals']
-  target_instrument: null
-  num_epochs: 1000
-  num_steps: 1000
-  optimizer: adam
-  lr: 9.0e-05
-  patience: 2
-  reduce_factor: 0.95
-  q: 0.95
-  coarse_loss_clip: true
-  ema_momentum: 0.999
-  other_fix: false # it's needed for checking on multisong dataset if other is actually instrumental
-  use_amp: false # 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
-
-inference:
-  num_overlap: 4
-  batch_size: 8
-
-model: hdemucs
-
-hdemucs:  # see demucs/hdemucs.py for a detailed description
-  channels: 48
-  channels_time: null
-  growth: 2
-  nfft: 4096
-  wiener_iters: 0
-  end_iters: 0
-  wiener_residual: False
-  cac: True
-  depth: 6
-  rewrite: True
-  hybrid: True
-  hybrid_old: False
-  multi_freqs: []
-  multi_freqs_depth: 3
-  freq_emb: 0.2
-  emb_scale: 10
-  emb_smooth: True
-  kernel_size: 8
-  stride: 4
-  time_stride: 2
-  context: 1
-  context_enc: 0
-  norm_starts: 4
-  norm_groups: 4
-  dconv_mode: 1
-  dconv_depth: 2
-  dconv_comp: 4
-  dconv_attn: 4
-  dconv_lstm: 4
-  dconv_init: 0.001
-  rescale: 0.1

configs/config_musdb18_htdemucs.yaml

@@ -1,119 +0,0 @@
-audio:
-  chunk_size: 485100 # samplerate * segment
-  min_mean_abs: 0.001
-  hop_length: 1024
-
-training:
-  batch_size: 8
-  gradient_accumulation_steps: 1
-  grad_clip: 0
-  segment: 11
-  shift: 1
-  samplerate: 44100
-  channels: 2
-  normalize: true
-  instruments: ['drums', 'bass', 'other', 'vocals']
-  target_instrument: null
-  num_epochs: 1000
-  num_steps: 1000
-  optimizer: adam
-  lr: 9.0e-05
-  patience: 2
-  reduce_factor: 0.95
-  q: 0.95
-  coarse_loss_clip: true
-  ema_momentum: 0.999
-  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
-
-inference:
-  num_overlap: 4
-  batch_size: 8
-
-model: htdemucs
-
-htdemucs:  # see demucs/htdemucs.py for a detailed description
-  # Channels
-  channels: 48
-  channels_time:
-  growth: 2
-  # STFT
-  num_subbands: 1
-  nfft: 4096
-  wiener_iters: 0
-  end_iters: 0
-  wiener_residual: false
-  cac: true
-  # Main structure
-  depth: 4
-  rewrite: true
-  # Frequency Branch
-  multi_freqs: []
-  multi_freqs_depth: 3
-  freq_emb: 0.2
-  emb_scale: 10
-  emb_smooth: true
-  # Convolutions
-  kernel_size: 8
-  stride: 4
-  time_stride: 2
-  context: 1
-  context_enc: 0
-  # normalization
-  norm_starts: 4
-  norm_groups: 4
-  # DConv residual branch
-  dconv_mode: 3
-  dconv_depth: 2
-  dconv_comp: 8
-  dconv_init: 1e-3
-  # Before the Transformer
-  bottom_channels: 512
-  # CrossTransformer
-  # ------ Common to all
-  # Regular parameters
-  t_layers: 5
-  t_hidden_scale: 4.0
-  t_heads: 8
-  t_dropout: 0.0
-  t_layer_scale: True
-  t_gelu: True
-  # ------------- Positional Embedding
-  t_emb: sin
-  t_max_positions: 10000 # for the scaled embedding
-  t_max_period: 10000.0
-  t_weight_pos_embed: 1.0
-  t_cape_mean_normalize: True
-  t_cape_augment: True
-  t_cape_glob_loc_scale: [5000.0, 1.0, 1.4]
-  t_sin_random_shift: 0
-  # ------------- norm before a transformer encoder
-  t_norm_in: True
-  t_norm_in_group: False
-  # ------------- norm inside the encoder
-  t_group_norm: False
-  t_norm_first: True
-  t_norm_out: True
-  # ------------- optim
-  t_weight_decay: 0.0
-  t_lr:
-  # ------------- sparsity
-  t_sparse_self_attn: False
-  t_sparse_cross_attn: False
-  t_mask_type: diag
-  t_mask_random_seed: 42
-  t_sparse_attn_window: 400
-  t_global_window: 100
-  t_sparsity: 0.95
-  t_auto_sparsity: False
-  # Cross Encoder First (False)
-  t_cross_first: False
-  # Weight init
-  rescale: 0.1
-

configs/config_musdb18_mdx23c.yaml

@@ -1,182 +0,0 @@
-audio:
-  chunk_size: 261120
-  dim_f: 4096
-  dim_t: 256
-  hop_length: 1024
-  n_fft: 8192
-  num_channels: 2
-  sample_rate: 44100
-  min_mean_abs: 0.001
-
-model:
-  act: gelu
-  bottleneck_factor: 4
-  growth: 128
-  norm: InstanceNorm
-  num_blocks_per_scale: 2
-  num_channels: 128
-  num_scales: 5
-  num_subbands: 4
-  scale:
-  - 2
-  - 2
-
-training:
-  batch_size: 6
-  gradient_accumulation_steps: 1
-  grad_clip: 0
-  instruments:
-  - vocals
-  - bass
-  - drums
-  - other
-  lr: 9.0e-05
-  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: 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"
-
-    # pedalboard reverb block
-    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
-
-    # pedalboard chorus block
-    pedalboard_chorus: 0.01
-    pedalboard_chorus_rate_hz_min: 1.0
-    pedalboard_chorus_rate_hz_max: 7.0
-    pedalboard_chorus_depth_min: 0.25
-    pedalboard_chorus_depth_max: 0.95
-    pedalboard_chorus_centre_delay_ms_min: 3
-    pedalboard_chorus_centre_delay_ms_max: 10
-    pedalboard_chorus_feedback_min: 0.0
-    pedalboard_chorus_feedback_max: 0.5
-    pedalboard_chorus_mix_min: 0.1
-    pedalboard_chorus_mix_max: 0.9
-
-    # pedalboard phazer block
-    pedalboard_phazer: 0.01
-    pedalboard_phazer_rate_hz_min: 1.0
-    pedalboard_phazer_rate_hz_max: 10.0
-    pedalboard_phazer_depth_min: 0.25
-    pedalboard_phazer_depth_max: 0.95
-    pedalboard_phazer_centre_frequency_hz_min: 200
-    pedalboard_phazer_centre_frequency_hz_max: 12000
-    pedalboard_phazer_feedback_min: 0.0
-    pedalboard_phazer_feedback_max: 0.5
-    pedalboard_phazer_mix_min: 0.1
-    pedalboard_phazer_mix_max: 0.9
-
-    # pedalboard distortion block
-    pedalboard_distortion: 0.01
-    pedalboard_distortion_drive_db_min: 1.0
-    pedalboard_distortion_drive_db_max: 25.0
-
-    # pedalboard pitch shift block
-    pedalboard_pitch_shift: 0.01
-    pedalboard_pitch_shift_semitones_min: -7
-    pedalboard_pitch_shift_semitones_max: 7
-
-    # pedalboard resample block
-    pedalboard_resample: 0.01
-    pedalboard_resample_target_sample_rate_min: 4000
-    pedalboard_resample_target_sample_rate_max: 44100
-
-    # pedalboard bitcrash block
-    pedalboard_bitcrash: 0.01
-    pedalboard_bitcrash_bit_depth_min: 4
-    pedalboard_bitcrash_bit_depth_max: 16
-
-    # pedalboard mp3 compressor block
-    pedalboard_mp3_compressor: 0.01
-    pedalboard_mp3_compressor_pedalboard_mp3_compressor_min: 0
-    pedalboard_mp3_compressor_pedalboard_mp3_compressor_max: 9.999
-
-  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
-  bass:
-    pitch_shift: 0.1
-    pitch_shift_min_semitones: -2
-    pitch_shift_max_semitones: 2
-    seven_band_parametric_eq: 0.25
-    seven_band_parametric_eq_min_gain_db: -3
-    seven_band_parametric_eq_max_gain_db: 6
-    tanh_distortion: 0.2
-    tanh_distortion_min: 0.1
-    tanh_distortion_max: 0.5
-  drums:
-    pitch_shift: 0.33
-    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: 0.33
-    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: 0.01
-    time_stretch_min_rate: 0.8
-    time_stretch_max_rate: 1.25
-
-
-inference:
-  batch_size: 1
-  dim_t: 256
-  num_overlap: 4

configs/config_musdb18_mel_band_roformer.yaml

@@ -1,73 +0,0 @@
-audio:
-  chunk_size: 131584
-  dim_f: 1024
-  dim_t: 256
-  hop_length: 512
-  n_fft: 2048
-  num_channels: 2
-  sample_rate: 44100
-  min_mean_abs: 0.001
-
-model:
-  dim: 192
-  depth: 8
-  stereo: true
-  num_stems: 1
-  time_transformer_depth: 1
-  freq_transformer_depth: 1
-  linear_transformer_depth: 0
-  num_bands: 60
-  dim_head: 64
-  heads: 8
-  attn_dropout: 0.1
-  ff_dropout: 0.1
-  flash_attn: True
-  dim_freqs_in: 1025
-  sample_rate: 44100 # needed for mel filter bank from librosa
-  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
-
-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: vocals
-  num_epochs: 1000
-  num_steps: 1000
-  q: 0.95
-  coarse_loss_clip: true
-  ema_momentum: 0.999
-  optimizer: adam
-  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
-
-inference:
-  batch_size: 1
-  dim_t: 256
-  num_overlap: 4

configs/config_musdb18_scnet.yaml

@@ -1,64 +0,0 @@
-audio:
-  chunk_size: 264600
-  num_channels: 2
-  sample_rate: 44100
-  min_mean_abs: 0.001
-
-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: 4
-
-  n_fft: 4096
-  hop_length: 1024
-  win_length: 4096
-  stft_normalized: false
-
-  use_mamba: true
-  d_state: 16
-  d_conv: 4
-  d_expand: 2
-
-training:
-  batch_size: 10
-  gradient_accumulation_steps: 1
-  grad_clip: 0
-  instruments:
-    - vocals
-    - bass
-    - drums
-    - 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: 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
-
-inference:
-  batch_size: 1
-  dim_t: 256
-  num_overlap: 4

configs/config_musdb18_segm_models.yaml

@@ -1,92 +0,0 @@
-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

configs/config_musdb18_torchseg.yaml

@@ -1,92 +0,0 @@
-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: maxvit_tiny_tf_512 # look with torchseg.list_encoders(). Currently 858 available
-  decoder_type: unet # unet, fpn
-  act: gelu
-  num_channels: 128
-  num_subbands: 8
-
-training:
-  batch_size: 18
-  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

configs/config_vocals_bandit_bsrnn_multi_mus64.yaml

@@ -1,73 +0,0 @@
-name: "MultiMaskMultiSourceBandSplitRNN"
-audio:
-  chunk_size: 264600
-  num_channels: 2
-  sample_rate: 44100
-  min_mean_abs: 0.001
-
-model:
-  in_channel: 1
-  stems: ['vocals', 'other']
-  band_specs: "musical"
-  n_bands: 64
-  fs: 44100
-  require_no_overlap: false
-  require_no_gap: true
-  normalize_channel_independently: false
-  treat_channel_as_feature: true
-  n_sqm_modules: 8
-  emb_dim: 128
-  rnn_dim: 256
-  bidirectional: true
-  rnn_type: "GRU"
-  mlp_dim: 512
-  hidden_activation: "Tanh"
-  hidden_activation_kwargs: null
-  complex_mask: true
-  n_fft: 2048
-  win_length: 2048
-  hop_length: 512
-  window_fn: "hann_window"
-  wkwargs: null
-  power: null
-  center: true
-  normalized: true
-  pad_mode: "constant"
-  onesided: true
-
-training:
-  batch_size: 4
-  gradient_accumulation_steps: 4
-  grad_clip: 0
-  instruments:
-  - vocals
-  - other
-  lr: 9.0e-05
-  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: 1
-  dim_t: 256
-  num_overlap: 4

configs/config_vocals_bs_roformer.yaml

@@ -1,138 +0,0 @@
-audio:
-  chunk_size: 131584
-  dim_f: 1024
-  dim_t: 256
-  hop_length: 512
-  n_fft: 2048
-  num_channels: 2
-  sample_rate: 44100
-  min_mean_abs: 0.001
-
-model:
-  dim: 192
-  depth: 6
-  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: 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
-
-training:
-  batch_size: 10
-  gradient_accumulation_steps: 1
-  grad_clip: 0
-  instruments:
-  - vocals
-  - other
-  lr: 5.0e-05
-  patience: 2
-  reduce_factor: 0.95
-  target_instrument: vocals
-  num_epochs: 1000
-  num_steps: 1000
-  q: 0.95
-  coarse_loss_clip: true
-  ema_momentum: 0.999
-  optimizer: adam
-  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
-
-inference:
-  batch_size: 1
-  dim_t: 256
-  num_overlap: 4

configs/config_vocals_htdemucs.yaml

@@ -1,123 +0,0 @@
-audio:
-  chunk_size: 485100 # samplerate * segment
-  min_mean_abs: 0.001
-  hop_length: 1024
-
-training:
-  batch_size: 10
-  gradient_accumulation_steps: 1
-  grad_clip: 0
-  segment: 11
-  shift: 1
-  samplerate: 44100
-  channels: 2
-  normalize: true
-  instruments: ['vocals', 'other']
-  target_instrument: null
-  num_epochs: 1000
-  num_steps: 1000
-  optimizer: adam
-  lr: 9.0e-05
-  patience: 2
-  reduce_factor: 0.95
-  q: 0.95
-  coarse_loss_clip: true
-  ema_momentum: 0.999
-  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: [0.2, 0.02]
-  mixup_loudness_min: 0.5
-  mixup_loudness_max: 1.5
-
-inference:
-  num_overlap: 2
-  batch_size: 8
-
-model: htdemucs
-
-htdemucs:  # see demucs/htdemucs.py for a detailed description
-  # Channels
-  channels: 48
-  channels_time:
-  growth: 2
-  # STFT
-  num_subbands: 1
-  nfft: 4096
-  wiener_iters: 0
-  end_iters: 0
-  wiener_residual: false
-  cac: true
-  # Main structure
-  depth: 4
-  rewrite: true
-  # Frequency Branch
-  multi_freqs: []
-  multi_freqs_depth: 3
-  freq_emb: 0.2
-  emb_scale: 10
-  emb_smooth: true
-  # Convolutions
-  kernel_size: 8
-  stride: 4
-  time_stride: 2
-  context: 1
-  context_enc: 0
-  # normalization
-  norm_starts: 4
-  norm_groups: 4
-  # DConv residual branch
-  dconv_mode: 3
-  dconv_depth: 2
-  dconv_comp: 8
-  dconv_init: 1e-3
-  # Before the Transformer
-  bottom_channels: 512
-  # CrossTransformer
-  # ------ Common to all
-  # Regular parameters
-  t_layers: 5
-  t_hidden_scale: 4.0
-  t_heads: 8
-  t_dropout: 0.0
-  t_layer_scale: True
-  t_gelu: True
-  # ------------- Positional Embedding
-  t_emb: sin
-  t_max_positions: 10000 # for the scaled embedding
-  t_max_period: 10000.0
-  t_weight_pos_embed: 1.0
-  t_cape_mean_normalize: True
-  t_cape_augment: True
-  t_cape_glob_loc_scale: [5000.0, 1.0, 1.4]
-  t_sin_random_shift: 0
-  # ------------- norm before a transformer encoder
-  t_norm_in: True
-  t_norm_in_group: False
-  # ------------- norm inside the encoder
-  t_group_norm: False
-  t_norm_first: True
-  t_norm_out: True
-  # ------------- optim
-  t_weight_decay: 0.0
-  t_lr:
-  # ------------- sparsity
-  t_sparse_self_attn: False
-  t_sparse_cross_attn: False
-  t_mask_type: diag
-  t_mask_random_seed: 42
-  t_sparse_attn_window: 400
-  t_global_window: 100
-  t_sparsity: 0.95
-  t_auto_sparsity: False
-  # Cross Encoder First (False)
-  t_cross_first: False
-  # Weight init
-  rescale: 0.1
-

configs/config_vocals_mdx23c.yaml

@@ -1,95 +0,0 @@
-audio:
-  chunk_size: 261120
-  dim_f: 4096
-  dim_t: 256
-  hop_length: 1024
-  n_fft: 8192
-  num_channels: 2
-  sample_rate: 44100
-  min_mean_abs: 0.001
-
-model:
-  act: gelu
-  bottleneck_factor: 4
-  growth: 128
-  norm: InstanceNorm
-  num_blocks_per_scale: 2
-  num_channels: 128
-  num_scales: 5
-  num_subbands: 4
-  scale:
-  - 2
-  - 2
-
-training:
-  batch_size: 6
-  gradient_accumulation_steps: 1
-  grad_clip: 0
-  instruments:
-  - vocals
-  - other
-  lr: 9.0e-05
-  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
-
-  # 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: 256
-  num_overlap: 4

configs/config_vocals_mel_band_roformer.yaml

@@ -1,77 +0,0 @@
-audio:
-  chunk_size: 131584
-  dim_f: 1024
-  dim_t: 256
-  hop_length: 512
-  n_fft: 2048
-  num_channels: 2
-  sample_rate: 44100
-  min_mean_abs: 0.001
-
-model:
-  dim: 192
-  depth: 8
-  stereo: true
-  num_stems: 1
-  time_transformer_depth: 1
-  freq_transformer_depth: 1
-  linear_transformer_depth: 0
-  num_bands: 60
-  dim_head: 64
-  heads: 8
-  attn_dropout: 0.1
-  ff_dropout: 0.1
-  flash_attn: True
-  dim_freqs_in: 1025
-  sample_rate: 44100  # needed for mel filter bank from librosa
-  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
-
-training:
-  batch_size: 7
-  gradient_accumulation_steps: 1
-  grad_clip: 0
-  instruments:
-  - vocals
-  - other
-  lr: 5.0e-05
-  patience: 2
-  reduce_factor: 0.95
-  target_instrument: vocals
-  num_epochs: 1000
-  num_steps: 1000
-  q: 0.95
-  coarse_loss_clip: true
-  ema_momentum: 0.999
-  optimizer: adam
-  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
-
-inference:
-  batch_size: 1
-  dim_t: 256
-  num_overlap: 4

configs/config_vocals_scnet.yaml

@@ -1,71 +0,0 @@
-audio:
-  chunk_size: 264600
-  num_channels: 2
-  sample_rate: 44100
-  min_mean_abs: 0.000
-
-model:
-  sources: ['vocals', 'other']
-  audio_channels: 2
-  # dims: [4, 32, 64, 128] # small version
-  dims: [4, 64, 128, 256]
-  nfft: 4096
-  hop_size: 1024
-  win_size: 4096
-  normalized: True
-  band_configs: {
-    'low': { 'SR': .175, 'stride': 1, 'kernel': 3 },
-    'mid': { 'SR': .392, 'stride': 4, 'kernel': 4 },
-    'high': { 'SR': .433, 'stride': 16, 'kernel': 16 }
-  }
-  conv_depths: [3, 2, 1]
-  compress: 4
-  conv_kernel: 3
-  # Dual-path RNN
-  num_dplayer: 6
-  expand: 1
-  # mamba
-  use_mamba: False
-  mamba_config: {
-    'd_stat': 16,
-    'd_conv': 4,
-    'd_expand': 2
-  }
-
-training:
-  batch_size: 4
-  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

configs/config_vocals_scnet_unofficial.yaml

@@ -1,62 +0,0 @@
-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

configs/config_vocals_segm_models.yaml

@@ -1,78 +0,0 @@
-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
-
-loss_multistft:
-  fft_sizes:
-  - 1024
-  - 2048
-  - 4096
-  hop_sizes:
-  - 512
-  - 1024
-  - 2048
-  win_lengths:
-  - 1024
-  - 2048
-  - 4096
-  window: "hann_window"
-  scale: "mel"
-  n_bins: 128
-  sample_rate: 44100
-  perceptual_weighting: true
-  w_sc: 1.0
-  w_log_mag: 1.0
-  w_lin_mag: 0.0
-  w_phs: 0.0
-  mag_distance: "L1"
-
-
-training:
-  batch_size: 8
-  gradient_accumulation_steps: 1
-  grad_clip: 0
-  instruments:
-  - vocals
-  - 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: 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: 1
-  dim_t: 512
-  num_overlap: 4

configs/config_vocals_swin_upernet.yaml

@@ -1,50 +0,0 @@
-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:
-  act: gelu
-  num_channels: 16
-  num_subbands: 8
-
-training:
-  batch_size: 14
-  gradient_accumulation_steps: 4
-  grad_clip: 0
-  instruments:
-  - vocals
-  - other
-  lr: 3.0e-05
-  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: adamw
-  other_fix: true # it's needed for checking on multisong dataset if other is actually instrumental
-
-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: 1
-  dim_t: 512
-  num_overlap: 4

configs/config_vocals_torchseg.yaml

@@ -1,58 +0,0 @@
-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: 0.000
-
-model:
-  encoder_name: maxvit_tiny_tf_512 # look with torchseg.list_encoders(). Currently 858 available
-  decoder_type: unet # unet, fpn
-  act: gelu
-  num_channels: 128
-  num_subbands: 8
-
-training:
-  batch_size: 18
-  gradient_accumulation_steps: 1
-  grad_clip: 1.0
-  instruments:
-  - vocals
-  - other
-  lr: 1.0e-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: false # 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)
-
-inference:
-  batch_size: 8
-  dim_t: 512
-  num_overlap: 2

configs/viperx/model_bs_roformer_ep_317_sdr_12.9755.yaml

@@ -1,126 +0,0 @@
-audio:
-  chunk_size: 352800
-  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: 512
-  depth: 12
-  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: 2
-  gradient_accumulation_steps: 1
-  grad_clip: 0
-  instruments:
-  - vocals
-  - other
-  lr: 1.0e-05
-  patience: 2
-  reduce_factor: 0.95
-  target_instrument: vocals
-  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
-
-inference:
-  batch_size: 4
-  dim_t: 801
-  num_overlap: 2

configs/viperx/model_bs_roformer_ep_937_sdr_10.5309.yaml

@@ -1,138 +0,0 @@
-audio:
-  chunk_size: 131584
-  dim_f: 1024
-  dim_t: 256
-  hop_length: 512
-  n_fft: 2048
-  num_channels: 2
-  sample_rate: 44100
-  min_mean_abs: 0.001
-
-model:
-  dim: 384
-  depth: 12
-  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: 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
-
-training:
-  batch_size: 4
-  gradient_accumulation_steps: 1
-  grad_clip: 0
-  instruments:
-  - vocals
-  - other
-  lr: 5.0e-05
-  patience: 2
-  reduce_factor: 0.95
-  target_instrument: other
-  num_epochs: 1000
-  num_steps: 1000
-  q: 0.95
-  coarse_loss_clip: true
-  ema_momentum: 0.999
-  optimizer: adam
-  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
-
-inference:
-  batch_size: 8
-  dim_t: 512
-  num_overlap: 2

configs/viperx/model_mel_band_roformer_ep_3005_sdr_11.4360.yaml

@@ -1,65 +0,0 @@
-audio:
-  chunk_size: 352800
-  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: 384
-  depth: 12
-  stereo: true
-  num_stems: 1
-  time_transformer_depth: 1
-  freq_transformer_depth: 1
-  linear_transformer_depth: 0
-  num_bands: 60
-  dim_head: 64
-  heads: 8
-  attn_dropout: 0.1
-  ff_dropout: 0.1
-  flash_attn: True
-  dim_freqs_in: 1025
-  sample_rate: 44100  # needed for mel filter bank from librosa
-  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: 8
-  grad_clip: 0
-  instruments:
-  - vocals
-  - other
-  lr: 4.0e-05
-  patience: 2
-  reduce_factor: 0.95
-  target_instrument: vocals
-  num_epochs: 1000
-  num_steps: 1000
-  q: 0.95
-  coarse_loss_clip: true
-  ema_momentum: 0.999
-  optimizer: adam
-  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
-
-inference:
-  batch_size: 4
-  dim_t: 801
-  num_overlap: 2