code: def training_scope(**kwargs):
      """Defines MobilenetV2 training scope.
  
      Usage:
         with tf.contrib.slim.arg_scope(mobilenet_v2.training_scope()):
           logits, endpoints = mobilenet_v2.mobilenet(input_tensor)
  
      with slim.
  
      Args:
        **kwargs: Passed to mobilenet.training_scope. The following parameters
        are supported:
          weight_decay- The weight decay to use for regularizing the model.
          stddev-  Standard deviation for initialization, if negative uses xavier.
          dropout_keep_prob- dropout keep probability
          bn_decay- decay for the batch norm moving averages.
  
      Returns:
        An `arg_scope` to use for the mobilenet v2 model.
      """
      return lib.training_scope(**kwargs)
  
file_path: MMdnn/mmdnn/conversion/examples/tensorflow/models/mobilenet/mobilenet_v2.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import tensorflow
  from mmdnn.conversion.examples.tensorflow.models.mobilenet import conv_blocks
  from mmdnn.conversion.examples.tensorflow.models.mobilenet import mobilenet
label_desc: Use image node_id 3 for calling a global function with example usage: training_scope() and returns: lib