3cba7783cb805459d26918be7a56b0e8b8fd3bc9,context_encoder.py,ContextEncoder,train,#ContextEncoder#Any#Any#Any#,140
Before Change
generated_missing_parts = self.generator.predict(masked_imgs)
imgs_x = np.vstack((missing_parts, generated_missing_parts) )
valid_y = np.array([1 ] * half_batch + [0 ] * half_batch).reshape(-1 , 1 )
After Change
gen_missing = self.generator.predict(masked_imgs)
valid = np.ones((half_batch, 1 ) )
fake = np.zeros((half_batch, 1 ))
d_loss_real = self.discriminator.train_on_batch(missing, valid)
d_loss_fake = self.discriminator.train_on_batch(gen_missing, fake)
d_loss = 0.5 * np.add(d_loss_real, d_loss_fake)
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 10
Instances Project Name: eriklindernoren/Keras-GAN
Commit Name: 3cba7783cb805459d26918be7a56b0e8b8fd3bc9
Time: 2017-07-17
Author: eriklindernoren@live.se
File Name: context_encoder.py
Class Name: ContextEncoder
Method Name: train
Project Name: eriklindernoren/Keras-GAN
Commit Name: 3cba7783cb805459d26918be7a56b0e8b8fd3bc9
Time: 2017-07-17
Author: eriklindernoren@live.se
File Name: gan.py
Class Name: GAN
Method Name: train
Project Name: eriklindernoren/Keras-GAN
Commit Name: 744353138995f1b15933be6ee2d39f7b83ee1b1f
Time: 2017-07-16
Author: eriklindernoren@live.se
File Name: dcgan.py
Class Name: DCGAN
Method Name: train