code: def class_logit(layer, label):
    
    def inner(T):
      if isinstance(label, int):
        class_n = label
      else:
        class_n = T("labels").index(label)
      logits = T(layer)
      logit = tf.reduce_sum(logits[:, class_n])
      return logit
    return inner
docs: Like channel, but for softmax layers.
  
    Args:
      layer: A layer name string.
      label: Either a string (refering to a label in model.labels) or an int
        label position.
  
    Returns:
      Objective maximizing a logit.