Adding new models (read description)

- BandSplit Roformer | 4-stems FT by SYH99999
- MelBand Roformer | 4-stems FT Large v1 by SYH99999
- MelBand Roformer | 4-stems FT Large v2 by SYH99999
- MelBand Roformer | 4-stems Large v1 by Aname
- MelBand Roformer | 4-stems XL v1 by Aname

models/Roformer/BandSplit/BandSplit_Roformer_4stems_FT_by_SYH99999.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a64c61c5972fe3fdf331d98f06bb4d6e237147c83a4bc71fd4e00e254c9b7652
+size 527245586

models/Roformer/BandSplit/config_BandSplit_Roformer_4stems_FT_by_SYH99999.yaml

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+audio:
+  chunk_size: 485100
+  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: 8
+  stereo: true
+  num_stems: 4
+  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
+  mlp_expansion_factor: 2
+  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: ['drums', 'bass', 'other', 'vocals']
+  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: 2
+  dim_t: 2048
+  num_overlap: 4

models/Roformer/MelBand/MelBand_Roformer_4stems_FT_Large_v1_by_SYH99999.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:590358e6abe3255d87d7173ca2e4005de082f14cbb466ea4c5ffedbcc3964506
+size 3764030874

models/Roformer/MelBand/MelBand_Roformer_4stems_FT_Large_v2_by_SYH99999.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:835ce9fa6651769c28ad5a2c87f9220b003a461d7d6c57ebe0898fff5479138c
+size 3764030874

models/Roformer/MelBand/MelBand_Roformer_4stems_Large_v1_by_Aname.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a2ca1ac95e203d2630994c3d4a0cebabd7160e70bb010adab794843340fb704f
+size 3764030874

models/Roformer/MelBand/MelBand_Roformer_4stems_XL_v1_by_Aname.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ca5f7c78543d84c369319f226b7337a6cc0b2e1a75d20409fc3ebde32686e94b
+size 6411087858

models/Roformer/MelBand/config_MelBand_Roformer_4stems_FT_Large_by_SYH99999.yaml

@@ -0,0 +1,69 @@
+audio:
+  chunk_size: 485100
+  dim_f: 1024
+  dim_t: 1101
+  hop_length: 882
+  n_fft: 2048
+  num_channels: 2
+  sample_rate: 44100
+  min_mean_abs: 0.000
+
+model:
+  dim: 384
+  depth: 8
+  stereo: true
+  num_stems: 4
+  linear_transformer_depth: 0
+  time_transformer_depth: 1
+  freq_transformer_depth: 1
+  num_bands: 60
+  dim_head: 64
+  heads: 8
+  attn_dropout: 0.0
+  ff_dropout: 0.0
+  flash_attn: true
+  dim_freqs_in: 2049
+  sample_rate: 44100  # needed for mel filter bank from librosa
+  stft_n_fft: 4096
+  stft_hop_length: 882
+  stft_win_length: 4096
+  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: True # Enable skip connection between transformer blocks - can solve problem with gradients and probably faster training
+
+training:
+  batch_size: 1
+  gradient_accumulation_steps: 1
+  grad_clip: 0
+  instruments: ['drums', 'bass', 'other', 'vocals']
+  lr: 1.0
+  patience: 3
+  reduce_factor: 0.95
+  target_instrument: null
+  num_epochs: 1000
+  num_steps: 1000
+  q: 0.95
+  coarse_loss_clip: false
+  ema_momentum: 0.999
+  optimizer: prodigy
+  read_metadata_procs: 8 # Number of processes to use during metadata reading for dataset. Can speed up metadata generation
+  normalize: false
+  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: 1101
+  num_overlap: 4
+  normalize: false

models/Roformer/MelBand/config_MelBand_Roformer_4stems_Large_v1_by_Aname.yaml

@@ -0,0 +1,167 @@
+audio:
+  chunk_size: 661500
+  dim_f: 1024
+  dim_t: 1101
+  hop_length: 882
+  n_fft: 4096
+  num_channels: 2
+  sample_rate: 44100
+  min_mean_abs: 0.0001
+
+model:
+  dim: 384
+  depth: 8
+  stereo: true
+  num_stems: 4
+  linear_transformer_depth: 0
+  time_transformer_depth: 1
+  freq_transformer_depth: 1
+  num_bands: 60
+  dim_head: 64
+  heads: 8
+  attn_dropout: 0.0
+  ff_dropout: 0.0
+  flash_attn: true
+  dim_freqs_in: 2049
+  sample_rate: 44100  # needed for mel filter bank from librosa
+  stft_n_fft: 4096
+  stft_hop_length: 882
+  stft_win_length: 4096
+  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: True # Enable skip connection between transformer blocks - can solve problem with gradients and probably faster training
+
+training:
+  batch_size: 1
+  gradient_accumulation_steps: 4
+  grad_clip: 0
+  instruments: ['drums', 'bass', 'other', 'vocals']
+  lr: 2.0e-05
+  patience: 2
+  reduce_factor: 0.95
+  target_instrument: null
+  num_epochs: 1000
+  num_steps: 300
+  q: 0.95
+  coarse_loss_clip: false
+  ema_momentum: 0.999
+  optimizer: adamw
+  read_metadata_procs: 8 # Number of processes to use during metadata reading for dataset. Can speed up metadata generation
+  normalize: false
+  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: false # enable or disable all augmentations (to fast disable if needed)
+  loudness: false # 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
+    - 0.002
+  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: 0.01 # inverse track (better lower probability)
+    random_polarity: 0.5 # polarity change (multiply waveform to -1)
+
+  vocals:
+      pitch_shift: 1.0
+      pitch_shift_min_semitones: -12
+      pitch_shift_max_semitones: 12
+      seven_band_parametric_eq: 0.5
+      seven_band_parametric_eq_min_gain_db: -80
+      seven_band_parametric_eq_max_gain_db: 9
+      tanh_distortion: 0.5
+      tanh_distortion_min: 0.1
+      tanh_distortion_max: 1
+      time_stretch: 1.0
+      time_stretch_min_rate: 0.5
+      time_stretch_max_rate: 2
+  bass:
+    pitch_shift: 1.0
+    pitch_shift_min_semitones: -6
+    pitch_shift_max_semitones: 6
+    seven_band_parametric_eq: 0.4
+    seven_band_parametric_eq_min_gain_db: -32
+    seven_band_parametric_eq_max_gain_db: 6
+    tanh_distortion: 1.0
+    tanh_distortion_min: 0.1
+    tanh_distortion_max: 0.5
+    time_stretch: 1.0
+    time_stretch_min_rate: 0.5
+    time_stretch_max_rate: 1.5
+  drums:
+    pitch_shift: 0.1
+    pitch_shift_min_semitones: -6
+    pitch_shift_max_semitones: 6
+    seven_band_parametric_eq: 0.5
+    seven_band_parametric_eq_min_gain_db: -24
+    seven_band_parametric_eq_max_gain_db: 12
+    tanh_distortion: 0.3
+    tanh_distortion_min: 0.1
+    tanh_distortion_max: 0.6
+    time_stretch: 1.0
+    time_stretch_min_rate: 0.333
+    time_stretch_max_rate: 1.5
+  other:
+    pitch_shift: 1.0
+    pitch_shift_min_semitones: -12
+    pitch_shift_max_semitones: 12
+    gaussian_noise: 0.4
+    gaussian_noise_min_amplitude: 0.001
+    gaussian_noise_max_amplitude: 0.15
+    time_stretch: 0.01
+    time_stretch_min_rate: 0.25
+    time_stretch_max_rate: 1.5
+
+inference:
+  batch_size: 1
+  dim_t: 256
+  num_overlap: 4
+  normalize: false
+
+loss_multistft:
+  fft_sizes:
+  - 1024
+  - 2048
+  - 4096
+  hop_sizes:
+  - 147
+  - 256
+  - 512
+  win_lengths:
+  - 1024
+  - 2048
+  - 4096
+  window: "hann_window"
+  scale: "mel"
+  n_bins: 128
+  sample_rate: 44100
+  perceptual_weighting: true
+  w_sc: 16.0
+  w_log_mag: 16.0
+  w_lin_mag: 16.0
+  w_phs: 0.0
+  mag_distance: "L1"

models/Roformer/MelBand/config_MelBand_Roformer_4stems_XL_v1_by_Aname.yaml

@@ -0,0 +1,167 @@
+audio:
+  chunk_size: 661500
+  dim_f: 1024
+  dim_t: 1101
+  hop_length: 882
+  n_fft: 4096
+  num_channels: 2
+  sample_rate: 44100
+  min_mean_abs: 0.0001
+
+model:
+  dim: 512
+  depth: 12
+  stereo: true
+  num_stems: 4
+  linear_transformer_depth: 0
+  time_transformer_depth: 1
+  freq_transformer_depth: 1
+  num_bands: 60
+  dim_head: 64
+  heads: 8
+  attn_dropout: 0.0
+  ff_dropout: 0.0
+  flash_attn: true
+  dim_freqs_in: 2049
+  sample_rate: 44100  # needed for mel filter bank from librosa
+  stft_n_fft: 4096
+  stft_hop_length: 882
+  stft_win_length: 4096
+  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: True # Enable skip connection between transformer blocks - can solve problem with gradients and probably faster training
+
+training:
+  batch_size: 1
+  gradient_accumulation_steps: 4
+  grad_clip: 0
+  instruments: ['drums', 'bass', 'other', 'vocals']
+  lr: 2.0e-05
+  patience: 2
+  reduce_factor: 0.95
+  target_instrument: null
+  num_epochs: 1000
+  num_steps: 300
+  q: 0.95
+  coarse_loss_clip: false
+  ema_momentum: 0.999
+  optimizer: adamw
+  read_metadata_procs: 8 # Number of processes to use during metadata reading for dataset. Can speed up metadata generation
+  normalize: false
+  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: false # enable or disable all augmentations (to fast disable if needed)
+  loudness: false # 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
+    - 0.002
+  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: 0.01 # inverse track (better lower probability)
+    random_polarity: 0.5 # polarity change (multiply waveform to -1)
+
+  vocals:
+      pitch_shift: 1.0
+      pitch_shift_min_semitones: -12
+      pitch_shift_max_semitones: 12
+      seven_band_parametric_eq: 0.5
+      seven_band_parametric_eq_min_gain_db: -80
+      seven_band_parametric_eq_max_gain_db: 9
+      tanh_distortion: 0.5
+      tanh_distortion_min: 0.1
+      tanh_distortion_max: 1
+      time_stretch: 1.0
+      time_stretch_min_rate: 0.5
+      time_stretch_max_rate: 2
+  bass:
+    pitch_shift: 1.0
+    pitch_shift_min_semitones: -6
+    pitch_shift_max_semitones: 6
+    seven_band_parametric_eq: 0.4
+    seven_band_parametric_eq_min_gain_db: -32
+    seven_band_parametric_eq_max_gain_db: 6
+    tanh_distortion: 1.0
+    tanh_distortion_min: 0.1
+    tanh_distortion_max: 0.5
+    time_stretch: 1.0
+    time_stretch_min_rate: 0.5
+    time_stretch_max_rate: 1.5
+  drums:
+    pitch_shift: 0.1
+    pitch_shift_min_semitones: -6
+    pitch_shift_max_semitones: 6
+    seven_band_parametric_eq: 0.5
+    seven_band_parametric_eq_min_gain_db: -24
+    seven_band_parametric_eq_max_gain_db: 12
+    tanh_distortion: 0.3
+    tanh_distortion_min: 0.1
+    tanh_distortion_max: 0.6
+    time_stretch: 1.0
+    time_stretch_min_rate: 0.333
+    time_stretch_max_rate: 1.5
+  other:
+    pitch_shift: 1.0
+    pitch_shift_min_semitones: -12
+    pitch_shift_max_semitones: 12
+    gaussian_noise: 0.4
+    gaussian_noise_min_amplitude: 0.001
+    gaussian_noise_max_amplitude: 0.15
+    time_stretch: 0.01
+    time_stretch_min_rate: 0.25
+    time_stretch_max_rate: 1.5
+
+inference:
+  batch_size: 1
+  dim_t: 256
+  num_overlap: 4
+  normalize: false
+
+loss_multistft:
+  fft_sizes:
+  - 1024
+  - 2048
+  - 4096
+  hop_sizes:
+  - 147
+  - 256
+  - 512
+  win_lengths:
+  - 1024
+  - 2048
+  - 4096
+  window: "hann_window"
+  scale: "mel"
+  n_bins: 128
+  sample_rate: 44100
+  perceptual_weighting: true
+  w_sc: 16.0
+  w_log_mag: 16.0
+  w_lin_mag: 16.0
+  w_phs: 0.0
+  mag_distance: "L1"