code: def tuple_mobilenetv3(is_large, is_mini):
      if is_mini is True:
          act_name = "Relu:0"
      else:
          act_name = "Mul:0"
  
      names = ["conv1/%s" % act_name]
      indices = [2]
      l = 3
  
      if is_large is True:
          names += ["conv2/out:0"]
          blocks = [2, 3, 4, 2, 3]
          k = 8
      else:
          names += ["conv2/pconv/bn/%s" % bn_name]
          blocks = [2, 3, 2, 3]
          if is_mini is True:
              k = 7
          else:
              k = 13
  
      indices += [k]
  
      for i, j in enumerate(blocks):
          names += ["conv%d/pconv/bn/%s" % (l, bn_name)]
          l += 1
          k += 8
          if is_mini is False:
              if (is_large is True and i in [1, 3, 4]) or (
                  is_large is False and i in [1, 2, 3, 4]
              ):
                  k += 6
          indices += [k]
          for _ in range(j - 1):
              names += ["conv%d/out:0" % l]
              l += 1
              k += 9
              if is_mini is False:
                  if (is_large is True and i in [1, 3, 4]) or (
                      is_large is False and i in [1, 2, 3, 4]
                  ):
                      k += 6
              indices += [k]
  
      indices += [k + 3, k + 4, k + 6]
      names += [
          "conv%d/%s" % (l, act_name),
          "pool/AvgPool:0",
          "conv%d/out:0" % (l + 1),
      ]
      return (indices, names, -16)
  
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 8 for calling a global function with example usage: tuple_mobilenetv3(is_large, is_mini) and returns: indices,  names,  unknown