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| author | nunzip <np.scarh@gmail.com> | 2019-02-27 18:50:58 +0000 | 
|---|---|---|
| committer | nunzip <np.scarh@gmail.com> | 2019-02-27 18:50:58 +0000 | 
| commit | 8268b98b17dc5190eb5c12c914ff4ffcc504400b (patch) | |
| tree | 522042995075c97ec9c4f006da8051443a340b80 | |
| parent | 7eec33f756cffee0c4526c7e3e6af71246dd0787 (diff) | |
| download | e4-gan-8268b98b17dc5190eb5c12c914ff4ffcc504400b.tar.gz e4-gan-8268b98b17dc5190eb5c12c914ff4ffcc504400b.tar.bz2 e4-gan-8268b98b17dc5190eb5c12c914ff4ffcc504400b.zip | |
Remove padding
| -rw-r--r-- | cgan.py | 5 | 
1 files changed, 0 insertions, 5 deletions
| @@ -203,11 +203,6 @@ class CGAN():          labels_test[i*100:] = i        train_data = self.generator.predict([noise_train, labels_train])        test_data = self.generator.predict([noise_test, labels_test]) -      test_data = np.pad(test_data, ((0,0),(2,2),(2,2),(0,0)), 'constant') -      train_data = np.pad(train_data, ((0,0),(2,2),(2,2),(0,0)), 'constant') -      labels_test = labels_test.flatten() -      labels_train = labels_train.flatten() -      print(train_data.shape, test_data.shape, labels_test.shape, labes_train.shape)        return train_data, test_data, labels_train, labels_test | 
