1aa6f71331656a09a2cc5a6f85a584ee362cedae,lib/discriminators/pyramid_discriminator.py,,discriminator,#Any#Any#Any#Any#Any#,6

Before Change

    filter_size_w = 2
    filter_size_h = 2
    filter = [1,filter_size_w,filter_size_h,1]
    stride = [1,filter_size_w,filter_size_h,1]
    result = tf.nn.avg_pool(result, ksize=filter, strides=stride, padding="SAME")

    result = batch_norm(config["batch_size"], name="d_expand_bn_end_"+str(i))(result)

After Change

      print("Discriminator pyramid layer:", net)

    net = tf.reshape(net, [config["batch_size"]*2, -1])
    net = batch_norm(config["batch_size"]*2, name="d_expand_bn_end_"+str(i))(net)
    net = activation(net)
    net = linear(net, int(1024), scope="d_fc_end1")
    net = batch_norm(config["batch_size"]*2, name="d_bn_end1")(net)
    net = activation(net)

    return net

Instances