4edcbc432d59b73cf79dd9a7364b42a1dafd1eff,infogan/infogan.py,INFOGAN,build_discriminator,#INFOGAN#,95

Before Change

        features = model(img)

        validity = Dense(1, activation="sigmoid")(features)

        def linmax(x):
            return K.maximum(x, -16)

After Change

        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.25))
        model.add(BatchNormalization(momentum=0.8))
        model.add(Conv2D(256, kernel_size=3, strides=2, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.25))
        model.add(BatchNormalization(momentum=0.8))

Instances