code: def tuple_efficientnet(
      index0, index1, blocks, addindices, biases=None
  ):
      indices = [index0] + list(range(index1, index1 + 12 * blocks, 12))
      names = [
          "block%d/pconv/bn/%s" % (i, bn_name)
          for i in range(len(indices))
      ]
      for i in addindices:
          for j in range(i, len(indices)):
              indices[j] += 2
          names.insert(
              i, "block%s/add:0" % names[i - 1].split("/")[0][5:]
          )
          indices.insert(i, indices[i - 1] + 2)
      if biases is not None:
          for b in biases:
              for j in range(b, len(indices)):
                  indices[j] -= 3
      return (indices, names, -10)
  
file_path: tensornets/tensornets/middles.py
imports: from __future__ import absolute_import
  from .version_utils import tf_equal_to
  from .version_utils import tf_later_than
label_desc: Use image node_id 9 for calling a global function with example usage: tuple_efficientnet(index0, index1, blocks, addindices, biases) and returns: indices,  names,  unknown