docs: def generate_training_command(model_folder):
      """Generate a string that contains a command with all necessary
         parameters to train the model."""
      update_if_outdated(model_folder)
      model_description_file = os.path.join(model_folder, "info.yml")
      # Read the model description file
      with open(model_description_file, 'r') as ymlfile:
          model_description = yaml.load(ymlfile)
  
      # Get the data paths (hdf5 files)
      project_root = utils.get_project_root()
      data = {}
      data['training'] = os.path.join(project_root,
                                      model_description["data-source"],
                                      "traindata.hdf5")
      data['testing'] = os.path.join(project_root,
                                     model_description["data-source"],
                                     "testdata.hdf5")
      data['validating'] = os.path.join(project_root,
                                        model_description["data-source"],
                                        "validdata.hdf5")
  
      # Get latest model file
      basename = "model"
      latest_model = utils.get_latest_working_model(model_folder)
  
      if latest_model == "":
          logging.error("There is no model with basename '%s'.", basename)
          return None
      else:
          logging.info("Model '%s' found.", latest_model)
          i = int(latest_model.split("-")[-1].split(".")[0])
          model_src = os.path.join(model_folder, "%s-%i.json" % (basename, i))
          model_target = os.path.join(model_folder,
                                      "%s-%i.json" % (basename, i+1))
  
      # generate the training command
      training = model_description['training']
      training = training.replace("{{testing}}", data['testing'])
      training = training.replace("{{training}}", data['training'])
      training = training.replace("{{validation}}", data['validating'])
      training = training.replace("{{src_model}}", model_src)
      training = training.replace("{{target_model}}", model_target)
      training = training.replace("{{nntoolkit}}", utils.get_nntoolkit())
      return training