559342a0aca96ac8bdf3fc0461b37877550539d6,train_uim2im.py,,main_train_imageEncoder,#,287

Before Change

        b_images = sess.run(net_gII.outputs, feed_dict={ // debug
                                t_caption : b_caption,
                                t_z : b_z})
        gen_images = sess.run(net_g2.outputs, feed_dict={
                                t_caption : b_caption,
                                t_z : b_z})
        print("b_images", np.min(b_images), np.max(b_images))
        print("gen_images", np.min(gen_images), np.max(gen_images))
        print("[*] Sampling images")
        combine_and_save_image_sets([b_images, gen_images], "samples/step2")

After Change

        stackD = stackD_256
    if is_E_256:
        cnn_encoder = cnn_encoder_256
        assert is_stackGAN == True

    t_caption = tf.placeholder(dtype=tf.int64, shape=[batch_size, None], name="caption_input")
    t_z = tf.placeholder(tf.float32, [batch_size, z_dim], name="z_noise")

Instances