Method sampler

stageI/trainer.py:125–131

(self)

            print("success")

    def sampler(self):
        c, _ = self.sample_encoded_context(self.embeddings)
        if cfg.TRAIN.FLAG:
            z = tf.zeros([self.batch_size, cfg.Z_DIM])  # Expect similar BGs
        else:
            z = tf.random_normal([self.batch_size, cfg.Z_DIM])
        self.fake_images = self.model.get_generator(tf.concat(1, [c, z]))

    def compute_losses(self, images, wrong_images, fake_images, embeddings):
        real_logit = self.model.get_discriminator(images, embeddings)