9010d90576d8da39f8c3be180cbccd0d1663f7c2,hypergan/discriminators/pyramid_nostride_discriminator.py,,discriminator,#Any#Any#Any#Any#Any#Any#Any#,29

Before Change

    xgs_conv = []
    for i in range(depth):
      //TODO better name for `batch_norm`?
      if batch_norm is not None:
          net = batch_norm(batch_size*2, name=prefix+"_expand_bn_"+str(i))(net)
      net = activation(net)
    
      //TODO: cross-d, overwritable
      // APPEND xs[i] and gs[i]

After Change

      //TODO: cross-d, overwritable
      // APPEND xs[i] and gs[i]
      if(i < len(xs) and i > 0):
        if config["layer_filter"]:
            x_filter_i = tf.concat(3, [xs[i], config["layer_filter"](None, xs[i])])
            g_filter_i = tf.concat(3, [gs[i], config["layer_filter"](None, xs[i])])
            xg = tf.concat(0, [x_filter_i, g_filter_i])
        else:
            xg = tf.concat(0, [xs[i], gs[i]])
        xg += tf.random_normal(xg.get_shape(), mean=0, stddev=config["noise_stddev"]*i, dtype=root_config["dtype"])

        xgs.append(xg)
  

Instances