config
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@ -2,10 +2,10 @@ _target_: enhancer.data.dataset.EnhancerDataset
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name : vctk
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name : vctk
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root_dir : /scratch/c.sistc3/DS_10283_2791
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root_dir : /scratch/c.sistc3/DS_10283_2791
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duration : 4.5
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duration : 4.5
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stride : 2
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stride : 0.5
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sampling_rate: 16000
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sampling_rate: 16000
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batch_size: 32
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batch_size: 32
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valid_minutes : 15
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valid_minutes : 25
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files:
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files:
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train_clean : clean_trainset_28spk_wav
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train_clean : clean_trainset_28spk_wav
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test_clean : clean_testset_wav
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test_clean : clean_testset_wav
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@ -1,7 +1,8 @@
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loss : mae
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loss : mae
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metric : [stoi,pesq,si-sdr]
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metric : [stoi,pesq,si-sdr]
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lr : 0.0003
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lr : 0.0003
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ReduceLr_patience : 5
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ReduceLr_patience : 10
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ReduceLr_factor : 0.2
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Early_stop : True
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ReduceLr_factor : 0.5
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min_lr : 0.000001
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min_lr : 0.000001
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EarlyStopping_factor : 10
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EarlyStopping_patience : 10
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@ -1,2 +1,2 @@
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experiment_name : shahules/enhancer
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experiment_name : shahules/enhancer
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run_name : Demucs + Vtck with stride + augmentations
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run_name : Demucs(ablation_study)
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@ -23,7 +23,7 @@ limit_test_batches: 1.0
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limit_train_batches: 1.0
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limit_train_batches: 1.0
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limit_val_batches: 1.0
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limit_val_batches: 1.0
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log_every_n_steps: 50
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log_every_n_steps: 50
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max_epochs: 200
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max_epochs: 250
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max_steps: -1
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max_steps: -1
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max_time: null
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max_time: null
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min_epochs: 1
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min_epochs: 1
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@ -136,6 +136,7 @@ class TaskDataset(pl.LightningDataModule):
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speaker_index = rng.choice(possible_indices)
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speaker_index = rng.choice(possible_indices)
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possible_indices.remove(speaker_index)
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possible_indices.remove(speaker_index)
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speaker_name = all_speakers[speaker_index]
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speaker_name = all_speakers[speaker_index]
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print(f"Selected f{speaker_name} for valid")
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file_indices = [
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file_indices = [
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i
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i
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for i, file in enumerate(data)
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for i, file in enumerate(data)
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