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authorVasil Zlatanov <v@skozl.com>2019-02-27 19:49:20 +0000
committerVasil Zlatanov <v@skozl.com>2019-02-27 19:49:20 +0000
commite7ac5212b90ac9058070c2d8f3e673cbc193ba08 (patch)
treee217f2a3646eba2e10b5f066bb68f99bf9dc8f10
parent7eae715bbac0a3ace5075e79e1b85b2ceb45c278 (diff)
parentf5e7e167119dff9e2bae122f44fc2172b0cae14b (diff)
downloade4-gan-e7ac5212b90ac9058070c2d8f3e673cbc193ba08.tar.gz
e4-gan-e7ac5212b90ac9058070c2d8f3e673cbc193ba08.tar.bz2
e4-gan-e7ac5212b90ac9058070c2d8f3e673cbc193ba08.zip
Also one_hot test
-rw-r--r--cgan.py5
1 files changed, 0 insertions, 5 deletions
diff --git a/cgan.py b/cgan.py
index d44f961..7bef77c 100644
--- a/cgan.py
+++ b/cgan.py
@@ -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