code: def neuron(layer_name, channel_n, x=None, y=None, batch=None):
      """Visualize a single neuron of a single channel.
  
      Defaults to the center neuron. When width and height are even numbers, we
      choose the neuron in the bottom right of the center 2x2 neurons.
  
      Odd width & height:               Even width & height:
  
      +---+---+---+                     +---+---+---+---+
      |   |   |   |                     |   |   |   |   |
      +---+---+---+                     +---+---+---+---+
      |   | X |   |                     |   |   |   |   |
      +---+---+---+                     +---+---+---+---+
      |   |   |   |                     |   |   | X |   |
      +---+---+---+                     +---+---+---+---+
                                        |   |   |   |   |
                                        +---+---+---+---+
      """
  
      @handle_batch(batch)
      def inner(T):
          layer = T(layer_name)
          layer = _extract_act_pos(layer, x, y)
          return tf.reduce_mean(layer[..., channel_n])
  
      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 3 for calling a global function with example usage: neuron(layer_name, channel_n, x, y, batch) and returns: inner, tf