code: def train(self):
      estimator = tf.estimator.Estimator(
          model_fn=self._model_fn,
          params=self.params,
          config=self.run_config,
          model_dir=self.params["model_dir"],
      )
  
      if self.profiling:
          hooks = [tf.train.ProfilerHook(50, output_dir="prof_dir")]
      else:
          hooks = []
      print(self.profiling, hooks)
      total_step = None
      try:
          total_step = self.params["total_step"]
      except:
          total_step = None
      estimator.train(
          input_fn=self.train_input_fn,
          hooks=hooks,
          # steps=self.params['total_step'])
          steps=total_step,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import json
  import numpy
  import tensorflow
  import tf_euler
label_desc: Use image node_id 11 for calling the BaseEstimator obj's underlying member method code with example usage: obj.train() without return types