Bandit Plus model added

README.md

@@ -12,7 +12,8 @@ Available models for training:
 * VitLarge23 based on [Segmentation Models Pytorch](https://github.com/qubvel/segmentation_models.pytorch). Key: `segm_models`. 
 * Band Split RoFormer [[Paper](https://arxiv.org/abs/2309.02612), [Repository](https://github.com/lucidrains/BS-RoFormer)] . Key: `bs_roformer`. 
 * Mel-Band RoFormer [[Paper](https://arxiv.org/abs/2310.01809), [Repository](https://github.com/lucidrains/BS-RoFormer)]. Key: `mel_band_roformer`.
-* Swin Upernet  [[Paper](https://arxiv.org/abs/2103.14030)] Key: `swin_upernet`.
+* Swin Upernet [[Paper](https://arxiv.org/abs/2103.14030)] Key: `swin_upernet`.
+* BandIt Plus [[Paper](https://arxiv.org/abs/2309.02539), [Repository](https://github.com/karnwatcharasupat/bandit)] Key: `bandit`.
 
  **Note 1**: For `segm_models` there are many different encoders is possible. [Look here](https://github.com/qubvel/segmentation_models.pytorch#encoders-).
 

configs/config_dnr_bandit_bsrnn_multi_mus64.yaml

@@ -0,0 +1,70 @@
+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
+  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: 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: 1
+  dim_t: 256
+  num_overlap: 4

configs/config_vocals_bandit_bsrnn_multi_mus64.yaml

@@ -0,0 +1,69 @@
+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
+  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: 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: 1
+  dim_t: 256
+  num_overlap: 4

inference.py

@@ -51,7 +51,7 @@ def run_folder(model, args, config, device, verbose=False):
 
 def proc_folder(args):
     parser = argparse.ArgumentParser()
-    parser.add_argument("--model_type", type=str, default='mdx23c', help="One of mdx23c, htdemucs, segm_models, mel_band_roformer, bs_roformer, swin_upernet")
+    parser.add_argument("--model_type", type=str, default='mdx23c', help="One of mdx23c, htdemucs, segm_models, mel_band_roformer, bs_roformer, swin_upernet, bandit")
     parser.add_argument("--config_path", type=str, help="path to config file")
     parser.add_argument("--start_check_point", type=str, default='', help="Initial checkpoint to valid weights")
     parser.add_argument("--input_folder", type=str, help="folder with mixtures to process")