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
