old_contents: # Copyright 2016 Hewlett Packard Enterprise Development LP
  #
  # 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.
  
  
  import os
  import errno
  import logging
  import tensorflow as tf
  
  #: Version string for current version
  version = '1.0.1-dev6'
  
  #: The log
  logger = logging.getLogger('opveclib')
  # for some strange reason, sphinx can't pull the docstring for this instance variable in the normal way
  logger.__doc__ = 'The opveclib logger'
  
  # set directories for cuda and operator cache
  cuda_directory = os.getenv('CUDA_HOME', '/usr/local/cuda')
  _base_cache_directory = os.getenv('OPVECLIB_HOME', os.path.join(os.path.expanduser('~'), '.opveclib'))
  
  #: Directory where cached operators are stored
  cache_directory = os.path.join(_base_cache_directory, version)
  
  # create the cache directory if it does not exist
  try:
      os.makedirs(cache_directory)
  except OSError as exception:
      if exception.errno != errno.EEXIST:
          raise
  
  #: The C++ compiler path
  cxx = os.getenv('OPVECLIB_CXX', 'g++')
  
  
  def clear_op_cache():
      """
      Delete all cached operators in the current cache directory. Generally used to make sure there are no stale
      operators in the cache when testing and debugging.
      """
      for filename in os.listdir(cache_directory):
          if filename[0] == 'f':
              os.remove(os.path.join(cache_directory, filename))
  
  #: Flag which indicates whether or not CUDA operators are enabled
  cuda_enabled = True
  
  # test whether we have cuda installed and if the tensorflow cuda version is installed
  if not os.path.exists(cuda_directory):
      cuda_enabled = False
      logger.info('CUDA directory not found - Running on CPU Only ***')
  elif not tf.test.is_built_with_cuda():
      cuda_enabled = False
      logger.info('TensorFlow CUDA version not installed - Running on CPU Only ***')
  else:
      logger.info('GPU version enabled')
  
new_contents: # Copyright 2016 Hewlett Packard Enterprise Development LP
  #
  # 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.
  
  
  import os
  import errno
  import logging
  import tensorflow as tf
  
  #: Version string for current version
  version = '1.0.2-dev0'
  
  #: The log
  logger = logging.getLogger('opveclib')
  # for some strange reason, sphinx can't pull the docstring for this instance variable in the normal way
  logger.__doc__ = 'The opveclib logger'
  
  # set directories for cuda and operator cache
  cuda_directory = os.getenv('CUDA_HOME', '/usr/local/cuda')
  _base_cache_directory = os.getenv('OPVECLIB_HOME', os.path.join(os.path.expanduser('~'), '.opveclib'))
  
  #: Directory where cached operators are stored
  cache_directory = os.path.join(_base_cache_directory, version)
  
  # create the cache directory if it does not exist
  try:
      os.makedirs(cache_directory)
  except OSError as exception:
      if exception.errno != errno.EEXIST:
          raise
  
  #: The C++ compiler path
  cxx = os.getenv('OPVECLIB_CXX', 'g++')
  
  
  def clear_op_cache():
      """
      Delete all cached operators in the current cache directory. Generally used to make sure there are no stale
      operators in the cache when testing and debugging.
      """
      for filename in os.listdir(cache_directory):
          if filename[0] == 'f':
              os.remove(os.path.join(cache_directory, filename))
  
  #: Flag which indicates whether or not CUDA operators are enabled
  cuda_enabled = True
  
  # test whether we have cuda installed and if the tensorflow cuda version is installed
  if not os.path.exists(cuda_directory):
      cuda_enabled = False
      logger.info('CUDA directory not found - Running on CPU Only ***')
  elif not tf.test.is_built_with_cuda():
      cuda_enabled = False
      logger.info('TensorFlow CUDA version not installed - Running on CPU Only ***')
  else:
      logger.info('GPU version enabled')
  
subject: update version to 1.0.2-dev0