code: def inception_resnet_v1_arg_scope(
      weight_decay=0.0, activation_fn=tf.nn.relu
  ):
      batch_norm_params = {
          # Decay for the moving averages.
          "decay": 0.995,
          # epsilon to prevent 0s in variance.
          "epsilon": 0.001,
          # force in-place updates of mean and variance estimates
          "updates_collections": None,
          # Moving averages ends up in the trainable variables collection
          "variables_collections": [tf.GraphKeys.TRAINABLE_VARIABLES],
      }
      with slim.arg_scope(
          [slim.conv2d, slim.fully_connected],
          weights_initializer=slim.initializers.xavier_initializer(),
          weights_regularizer=slim.l2_regularizer(weight_decay),
          normalizer_fn=slim.batch_norm,
          normalizer_params=batch_norm_params,
      ) as sc:
          return sc
  
file_path: MMdnn/mmdnn/conversion/examples/tensorflow/models/inception_resnet_v1.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  import tensorflow.contrib.slim
label_desc: Use image node_id 6 for calling a global function with example usage: inception_resnet_v1_arg_scope(weight_decay, activation_fn) and returns: sc