Update config.gin to keep required params only with explicit names

config.gin

@@ -1,98 +1,55 @@
-# Parameters for AudioDataModule:
-# ==============================================================================
-AudioDataModule.num_workers = 20
-
-# Parameters for AudioDataset:
-# ==============================================================================
-AudioDataset.half_precision = True
-AudioDataset.mono = True
-AudioDataset.new_freq = 16000
-AudioDataset.num_frames = 480000
-AudioDataset.orig_freq = 16000
-
-# Parameters for build_dev_datamodule:
-# ==============================================================================
-build_dev_datamodule.datamodule = @discotube
 
 # Parameters for build_module:
 # ==============================================================================
-build_module.ckpt_path = 'model.ckpt'
-build_module.module = @modules.maskingmodel.MaskingModel
-build_module.net = @nets.conformer.Conformer
-build_module.representation = @nets.melspectrogram.MelSpectrogram
-
-# Parameters for Conformer:
-# ==============================================================================
-Conformer.alpha_deepnorm = 2.6321480259049848
-Conformer.beta_deepnorm = 0.022386873579657126
-Conformer.conv_kernel_size = 5
-Conformer.depth = 24
-Conformer.dropout = 0.2
-Conformer.embed_dim = 1024
-Conformer.input_dropout = 0.0
-Conformer.mlp_ratio = 4.0
-Conformer.mlp_residual_factor = 4.0
-Conformer.num_heads = 8
-Conformer.num_patches = 460
-Conformer.use_deepnorm = True
-Conformer.use_rope = True
-
-# Parameters for CosineAnnealingCallback:
-# ==============================================================================
-CosineAnnealingCallback.eta_min = 1e-07
-CosineAnnealingCallback.warmup_steps = 30000
-
-# Parameters for DiscotubeAudioDataModule:
-# ==============================================================================
-DiscotubeAudioDataModule.batch_size = 32
-DiscotubeAudioDataModule.data_dir = ''
-DiscotubeAudioDataModule.filelist_train = ''
-DiscotubeAudioDataModule.filelist_val = ''
-
-# Parameters for MaskingModel:
-# ==============================================================================
-MaskingModel.codebook_dim = 16
-MaskingModel.codebook_size = 8192
-MaskingModel.diff_input = False
-MaskingModel.lr = 0.0001
-MaskingModel.mask_prob = 0.6
-MaskingModel.mask_seconds = 0.4
-MaskingModel.num_codebooks = 4
-MaskingModel.plot_tokens = False
-MaskingModel.seed = 0
-MaskingModel.weight_decay = 0.01
-
-# Parameters for MelSpectrogram:
-# ==============================================================================
-MelSpectrogram.freq_mask_param = 0
-MelSpectrogram.hop_len = 256
-MelSpectrogram.mel_scale = 'slaney'
-MelSpectrogram.n_mel = 96
-MelSpectrogram.norm = 'slaney'
-MelSpectrogram.norm_mean = 2.06755686098554
-MelSpectrogram.norm_std = 1.268292820667291
-MelSpectrogram.power = 2
-MelSpectrogram.sr = 16000
-MelSpectrogram.stretch_factor = 1
-MelSpectrogram.time_mask_param = 0
-MelSpectrogram.win_len = 512
-MelSpectrogram.patch_size = (96, 4)
-
-# Parameters for train:
-# ==============================================================================
-train.params = \
-    {'accelerator': 'gpu',
-     'devices': 4,
-     'log_every_n_steps': 50,
-     'max_steps': 400000,
-     'num_nodes': 1,
-     'num_sanity_val_steps': 0,
-     'precision': 'bf16-mixed',
-     'strategy': 'ddp_find_unused_parameters_true'}
-train.wandb_params = \
-    {'entity': 'mtg-upf',
-     'group': 'masking_conformer',
-     'name': 'mask_conformer_rope_multi4_large',
-     'offline': True,
-     'project': 'mtg-ssl',
-     'save_dir': '/gpfs/projects/upf97/logs/'}
+omar_rq.utils.build_module.ckpt_path = 'model.ckpt'
+omar_rq.utils.build_module.module = @omar_rq.modules.maskingmodel.MaskingModel
+omar_rq.utils.build_module.net = @omar_rq.nets.conformer.Conformer
+omar_rq.utils.build_module.representation = @omar_rq.nets.melspectrogram.MelSpectrogram
+
+# Parameters for omar_rq.nets.conformer.Conformer:
+# ==============================================================================
+omar_rq.nets.conformer.Conformer.alpha_deepnorm = 2.6321480259049848
+omar_rq.nets.conformer.Conformer.beta_deepnorm = 0.022386873579657126
+omar_rq.nets.conformer.Conformer.conv_kernel_size = 5
+omar_rq.nets.conformer.Conformer.depth = 24
+omar_rq.nets.conformer.Conformer.dropout = 0.2
+omar_rq.nets.conformer.Conformer.embed_dim = 1024
+omar_rq.nets.conformer.Conformer.input_dropout = 0.0
+omar_rq.nets.conformer.Conformer.mlp_ratio = 4.0
+omar_rq.nets.conformer.Conformer.mlp_residual_factor = 4.0
+omar_rq.nets.conformer.Conformer.num_heads = 8
+omar_rq.nets.conformer.Conformer.num_patches = 460
+omar_rq.nets.conformer.Conformer.patch_size = None
+omar_rq.nets.conformer.Conformer.use_deepnorm = True
+omar_rq.nets.conformer.Conformer.use_rope = True
+
+# Parameters for omar_rq.modules.maskingmodel.MaskingModel:
+# ==============================================================================
+omar_rq.modules.maskingmodel.MaskingModel.codebook_dim = 16
+omar_rq.modules.maskingmodel.MaskingModel.codebook_size = 8192
+omar_rq.modules.maskingmodel.MaskingModel.diff_input = False
+omar_rq.modules.maskingmodel.MaskingModel.input_representation = None
+omar_rq.modules.maskingmodel.MaskingModel.lr = 0.0001
+omar_rq.modules.maskingmodel.MaskingModel.mask_prob = 0.6
+omar_rq.modules.maskingmodel.MaskingModel.mask_seconds = 0.4
+omar_rq.modules.maskingmodel.MaskingModel.masking_noise_type = 'random_normal'
+omar_rq.modules.maskingmodel.MaskingModel.num_codebooks = 4
+omar_rq.modules.maskingmodel.MaskingModel.plot_tokens = False
+omar_rq.modules.maskingmodel.MaskingModel.quantizer_type = 'random_codebook'
+omar_rq.modules.maskingmodel.MaskingModel.seed = 0
+omar_rq.modules.maskingmodel.MaskingModel.weight_decay = 0.01
+
+# Parameters for omar_rq.nets.melspectrogram.MelSpectrogram:
+# ==============================================================================
+omar_rq.nets.melspectrogram.MelSpectrogram.freq_mask_param = 0
+omar_rq.nets.melspectrogram.MelSpectrogram.hop_len = 256
+omar_rq.nets.melspectrogram.MelSpectrogram.mel_scale = 'slaney'
+omar_rq.nets.melspectrogram.MelSpectrogram.n_mel = 96
+omar_rq.nets.melspectrogram.MelSpectrogram.norm = 'slaney'
+omar_rq.nets.melspectrogram.MelSpectrogram.norm_mean = 2.06755686098554
+omar_rq.nets.melspectrogram.MelSpectrogram.norm_std = 1.268292820667291
+omar_rq.nets.melspectrogram.MelSpectrogram.power = 2
+omar_rq.nets.melspectrogram.MelSpectrogram.sr = 16000
+omar_rq.nets.melspectrogram.MelSpectrogram.stretch_factor = 1
+omar_rq.nets.melspectrogram.MelSpectrogram.time_mask_param = 0
+omar_rq.nets.melspectrogram.MelSpectrogram.win_len = 512