Removed randomization process in generate_augmented_labelled_dataset(), at...

Removed randomization process in generate_augmented_labelled_dataset(), at this process is now done inside the model.

core/utils.py

@@ -96,7 +96,7 @@ def generate_augmented_labelled_dataset(signals, labels, convolve_mode='valid',
     if sounds is None:
         for i in range(n_augment):
             for j, signal in enumerate(signals):
-                augmented_signals.append([data_generator(signal)])
+                augmented_signals.append([signal])
             for i_label, label in enumerate(labels):
                 augmented_labels.append(label)
     else:
@@ -107,12 +107,11 @@ def generate_augmented_labelled_dataset(signals, labels, convolve_mode='valid',
                 signal, label = signal_label
                 if j % len(sounds) == 0:
                     np.random.shuffle(i_sounds)
-                randomized_hrir = data_generator(signal)
                 sound = np.zeros(shape=[len(sounds[0]), n_channels])
                 new_signals = []
                 for i_channel in range(n_channels):
                     sound[0:n_samples, i_channel] = sounds[j % len(sounds)][0:n_samples]
-                    convolved_sound = scipy.signal.convolve(in1=sound[:, i_channel], in2=randomized_hrir[:, i_channel],
+                    convolved_sound = scipy.signal.convolve(in1=sound[:, i_channel], in2=signal[:, i_channel],
                                                             mode=convolve_mode,
                                                             method='auto')
                     new_signals.append(convolved_sound)

scripts/train2.py

@@ -56,7 +56,7 @@ if __name__ == '__main__':
             if not 'convolve_mode' in exp_config.keys() or exp_config['convolve_mode'] == 'valid':
                 # the valid part from the convolved sound is sound[len(hrir)-1:-len(hrir)+1]
                 # hence we have to do len(hrir)-1 left and right zero padding so that the dirac belong to the result
-                n_zeros = 512-1+exp_config['model_config']['random_shift']['maxval']
+                n_zeros = 512-1
                 zeros = np.zeros(shape=(2, n_zeros))
                 sounds = np.concatenate([zeros, np.ones(shape=(2, 1)), zeros], axis=1)
                 training_sounds, test_sounds = np.array_split(sounds, 2, axis=0)