code: def class_logit(layer, label, batch=None):
      """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.
      """
  
      @handle_batch(batch)
      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
  
imports: from __future__ import absolute_import, division, print_function
  from decorator import decorator
  import numpy
  import tensorflow
  from lucid.optvis.objectives_util import _dot, _dot_cossim, _extract_act_pos, _make_arg_str, _T_force_NHWC, _T_handle_batch
label_desc: Use image node_id 20 for calling a global function with example usage: class_logit(layer, label, batch) and returns: inner, logit