INNER CODE UNIT · Python

build_gan_discriminator

zuruoke/watermark-removal · inpaint_model.py:124

    def build_gan_discriminator(
            self, batch, reuse=False, training=True):
        with tf.variable_scope('discriminator', reuse=reuse):
            d = self.build_sn_patch_gan_discriminator(
                batch, reuse=reuse, training=training)
            return d

    def build_graph_with_losses(
            self, FLAGS, batch_data, training=True, summary=False,
            reuse=False):
        if FLAGS.guided:
            batch_data, edge = batch_data
            edge = edge[:, :, :, 0:1] / 255.
            edge = tf.cast(edge > FLAGS.edge_threshold, tf.float32)
        batch_pos = batch_data / 127.5 - 1.
        # generate mask, 1 represents masked point
        bbox = random_bbox(FLAGS)
        regular_mask = bbox2mask(FLAGS, bbox, name='mask_c')

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