new_contents: """Logging utilities."""
  
  # Copyright 2015 The TensorFlow Authors. All Rights Reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  # ============================================================================
  #
  # Modifications copyright Jonathan de Bruin 2017
  
  import logging as _logging
  import sys as _sys
  
  # Determine whether we are in an interactive environment
  _interactive = False
  try:
      # This is only defined in interactive shells
      if _sys.ps1:
          _interactive = True
  except AttributeError:
      # Even now, we may be in an interactive shell with `python -i`.
      _interactive = _sys.flags.interactive
  
  # Scope the tensorflow logger to not conflict with users' loggers
  _logger = _logging.getLogger('recordlinkage')
  
  # If we are in an interactive environment (like jupyter), set loglevel to info
  # and pipe the output to stdout
  if _interactive:
      _logger.setLevel(_logger.INFO)
      _logging_target = _sys.stdout
  else:
      _logging_target = _sys.stderr
  
  # Add the output handler
  _handler = _logging.StreamHandler(_logging_target)
  _handler.setFormatter(_logging.Formatter(_logging.BASIC_FORMAT, None))
  _logger.addHandler(_handler)
  
  log = _logger.log
  debug = _logger.debug
  error = _logger.error
  fatal = _logger.fatal
  info = _logger.info
  warn = _logger.warn
  warning = _logger.warning
  
  
  def get_verbosity():
      """Return how much logging output will be produced."""
      return _logger.getEffectiveLevel()
  
  
  def set_verbosity(verbosity):
      """Sets the threshold for what messages will be logged."""
      _logger.setLevel(verbosity)
  
subject: Add logging module based on tensorflow