code: def _populate_inception_bottlenecks(scope):
      """Add Inception bottlenecks and their pre-Relu versions to the graph."""
      graph = tf.get_default_graph()
      for op in graph.get_operations():
          if op.name.startswith(scope + "/") and "Concat" in op.type:
              name = op.name.split("/")[1]
              pre_relus = []
              for tower in op.inputs[1:]:
                  if tower.op.type == "Relu":
                      tower = tower.op.inputs[0]
                  pre_relus.append(tower)
              concat_name = scope + "/" + name + "_pre_relu"
              _ = tf.concat(pre_relus, -1, name=concat_name)
  
file_path: lucid/lucid/modelzoo/other_models/InceptionV1.py
imports: from __future__ import absolute_import, division, print_function
  import tensorflow
  from lucid.modelzoo.vision_base import Model, _layers_from_list_of_dicts
label_desc: Use image node_id 1 for calling a global function with example usage: _populate_inception_bottlenecks(scope) without return types