code: def mobile_imagenet_config():
      return tf.contrib.training.HParams(
          stem_multiplier=1.0,
          dense_dropout_keep_prob=0.5,
          num_cells=12,
          filter_scaling_rate=2.0,
          drop_path_keep_prob=1.0,
          num_conv_filters=44,
          use_aux_head=1,
          num_reduction_layers=2,
          data_format="NHWC",
          skip_reduction_layer_input=0,
          total_training_steps=250000,
          use_bounded_activation=False,
      )
  
file_path: adanet/research/improve_nas/trainer/nasnet.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling a global function with example usage: mobile_imagenet_config() and returns: tf