class_docstr: A hook to capture metadata for a single step.
  Useful for performance debugging. It performs a full trace and saves
  run_metadata and Chrome timeline information to a file.
  
  Args:
    step: The step number to trace. The hook is only enable for this step.
code: def __init__(self, params, model_dir, run_config):
      super(MetadataCaptureHook, self).__init__(
          params, model_dir, run_config
      )
      self._active = False
      self._done = False
      self._global_step = None
      self._output_dir = os.path.abspath(self.model_dir)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import abc
  import os
  import numpy
  import six
  import yaml
  import tensorflow
  from tensorflow.python.training.basic_session_run_hooks import SecondOrStepTimer
  from tensorflow.python.training import session_manager
  from tensorflow.python.client import timeline
  from tensorflow import gfile
  from seq2seq.configurable import Configurable, abstractstaticmethod
  from seq2seq import graph_utils, global_vars
label_desc: Use image node_id 1 to create a new MetadataCaptureHook object from inherited base classes: TrainingHook with example: obj = MetadataCaptureHook(params, model_dir, run_config)