code: def make_t_image(param_f):
      if param_f is None:
          t_image = param.image(128)
      elif callable(param_f):
          t_image = param_f()
      elif isinstance(param_f, tf.Tensor):
          t_image = param_f
      else:
          raise TypeError(
              "Incompatible type for param_f, " + str(type(param_f))
          )
  
      if not isinstance(t_image, tf.Tensor):
          raise TypeError(
              "param_f should produce a Tensor, but instead created a "
              + str(type(t_image))
          )
      elif t_image.graph != tf.get_default_graph():
          raise TypeError(
              """param_f produced a t_image tensor belonging to a graph
                       that isn't the default graph for rendering. Did you
                       accidentally use render_vis when you meant to use
                       make_vis_T?"""
          )
      else:
          return t_image
  
file_path: lucid/lucid/optvis/render.py
imports: from __future__ import absolute_import, division, print_function
  from future.standard_library import install_aliases
  from builtins import range
  import numpy
  import tensorflow
  import logging
  from lucid.optvis import objectives, param, transform
  from lucid.misc.io import show
  from lucid.misc.redirected_relu_grad import redirected_relu_grad, redirected_relu6_grad
  from lucid.misc.gradient_override import gradient_override_map
label_desc: Use image node_id 4 for calling a global function with example usage: make_t_image(param_f) and returns: t_image