content: #    Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
  #
  #    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
  
  """
  PLEASE READ documentation/setting_up_paths.md FOR INFORMATION TO HOW TO SET THIS UP
  """
  
  nnUNet_raw = os.environ.get('nnUNet_raw')
  nnUNet_preprocessed = os.environ.get('nnUNet_preprocessed')
  nnUNet_results = os.environ.get('nnUNet_results')
  
  if nnUNet_raw is None:
      print("nnUNet_raw is not defined and nnU-Net can only be used on data for which preprocessed files "
            "are already present on your system. nnU-Net cannot be used for experiment planning and preprocessing like "
            "this. If this is not intended, please read documentation/setting_up_paths.md for information on how to set "
            "this up properly.")
  
  if nnUNet_preprocessed is None:
      print("nnUNet_preprocessed is not defined and nnU-Net can not be used for preprocessing "
            "or training. If this is not intended, please read documentation/setting_up_paths.md for information on how "
            "to set this up.")
  
  if nnUNet_results is None:
      print("nnUNet_results is not defined and nnU-Net cannot be used for training or "
            "inference. If this is not intended behavior, please read documentation/setting_up_paths.md for information "
            "on how to set this up.")
  