cf65784f7297dca491436112b9a5689ecd7533ec,acgan/acgan.py,ACGAN,train,#ACGAN#,121

Before Change

            idx = np.random.randint(0, X_train.shape[0], half_batch)
            imgs = X_train[idx]

            noise = np.random.normal(0, 1, (half_batch, 100))

            // The labels of the digits that the generator tries to create an
            // image representation of

After Change

            // The labels of the digits that the generator tries to create an
            // image representation of
            sampled_labels = np.random.randint(0, 10, (batch_size, 1))

            // Generate a half batch of new images
            gen_imgs = self.generator.predict([noise, sampled_labels])

Instances