def discriminator(self, X, reuse=False): with tf.variable_scope('discriminator', reuse=reuse): layer = Stacker(X) layer.conv_block(128, CONV_FILTER_5522, lrelu) layer.conv_block(256, CONV_FILTER_5522, lrelu) layer.reshape([self.batch_size, -1]) layer.linear(1) layer.sigmoid() return layer.last_layer
def discriminator(self, X, Y, reuse=False): with tf.variable_scope('discriminator', reuse=reuse): Y = linear(Y, self.input_h * self.input_w) Y = reshape(Y, [self.batch_size, self.input_h, self.input_w, 1]) layer = Stacker(tf.concat((X, Y), axis=3)) layer.conv_block(128, CONV_FILTER_5522, lrelu) layer.conv_block(256, CONV_FILTER_5522, lrelu) layer.reshape([self.batch_size, -1]) layer.linear(1) layer.sigmoid() return layer.last_layer