old_contents: # -*- coding: utf-8 -*-
  from __future__ import absolute_import, division, print_function
  
  from polyaxon_client.exceptions import PolyaxonClientException
  from polyaxon_client.tracking import Experiment
  from polyaxon_client import settings
  
  try:
      from tensorflow.train import LoggingTensorHook
  except ImportError:
      raise PolyaxonClientException('tensorflow is required to use PolyaxonLoggingTensorHook')
  
  class PolyaxonLoggingTensorHook(tf.train.LoggingTensorHook):
      """Hook that logs data to console and Polyaxon"""
  
      def __init__(self, tensors_dict, every_n_iter=None, every_n_secs=None):
          super(PolyaxonMetrics, self).__init__(tensors_dict,
                                                every_n_iter=every_n_iter,
                                                every_n_secs=every_n_secs)
          self.tensors_dict = tensors_dict.copy()
  
      def _log_tensors(self, tensor_values):
          super(PolyaxonMetrics, self)._log_tensors(tensor_values)
          if settings.IN_CLUSTER:
              for k in self.tensors_dict.keys():
                  self.tensors_dict[k] = tensor_values[k]
              experimet = Experiment()
              experimet.log_metrics(**self.tensors_dict)
  
new_contents: # -*- coding: utf-8 -*-
  from __future__ import absolute_import, division, print_function
  
  from polyaxon_client.exceptions import PolyaxonClientException
  from polyaxon_client.tracking import Experiment
  from polyaxon_client import settings
  
  try:
      from tensorflow.train import LoggingTensorHook
  except ImportError:
      raise PolyaxonClientException('tensorflow is required to use PolyaxonLoggingTensorHook')
  
  class PolyaxonLoggingTensorHook(tf.train.LoggingTensorHook):
      """Hook that logs data to console and Polyaxon"""
  
      def __init__(self, tensors_dict, every_n_iter=None, every_n_secs=None):
          super(PolyaxonLoggingTensorHook, self).__init__(tensors_dict,
                                                every_n_iter=every_n_iter,
                                                every_n_secs=every_n_secs)
          self.tensors_dict = tensors_dict.copy()
  
      def _log_tensors(self, tensor_values):
          super(PolyaxonMetrics, self)._log_tensors(tensor_values)
          if settings.IN_CLUSTER:
              for k in self.tensors_dict.keys():
                  self.tensors_dict[k] = tensor_values[k]
              experimet = Experiment()
              experimet.log_metrics(**self.tensors_dict)
  
subject: Update logging_tensor_hook.py