class_docstr: BaseApplication represents an interface.
  
  Each application ``type_str`` should support to use
  the standard training and inference driver.
class_docstr_tok: ["BaseApplication","represents","an","interface",".","Each","application","``","type_str","``","should","support","to","use","the","standard","training","and","inference","driver","."]
docstr: This function adds entries to parameter objects to enable
  the evaluation action to automatically read in the output of a
  previous inference run if inference is not explicitly specified.
  
  This can be used in an application if there is a data section
  entry in the configuration file that matches the inference output.
  In supervised learning, the reference data section would often
  match the inference output and could be used here. Otherwise,
  a template data section could be used.
  
  :param data_param:
  :param task_param:
  :param name:  name of input parameter to copy parameters from
  :return: modified data_param and task_param
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code: def add_inferred_output_like(self, data_param, task_param, name):
      """This function adds entries to parameter objects to enable
      the evaluation action to automatically read in the output of a
      previous inference run if inference is not explicitly specified.
  
      This can be used in an application if there is a data section
      entry in the configuration file that matches the inference output.
      In supervised learning, the reference data section would often
      match the inference output and could be used here. Otherwise,
      a template data section could be used.
  
      :param data_param:
      :param task_param:
      :param name:  name of input parameter to copy parameters from
      :return: modified data_param and task_param
      """
      print(task_param)
      # Add the data parameter
      if "inferred" not in data_param:
          data_name = vars(task_param)[name][0]
          inferred_param = Namespace(**vars(data_param[data_name]))
          inferred_param.csv_file = os.path.join(
              self.action_param.save_seg_dir, "inferred.csv"
          )
          data_param["inferred"] = inferred_param
      # Add the task parameter
      if "inferred" not in task_param or not task_param.inferred:
          task_param.inferred = ("inferred",)
      return data_param, task_param
  
imports: import os
  from argparse import Namespace
  import tensorflow
  from six import with_metaclass
  from niftynet.engine.signal import TRAIN, INFER, EVAL
label_desc: Use image node_id 6 for calling the BaseApplication obj's underlying member method code with example usage: obj.add_inferred_output_like(data_param, task_param, name) and returns: data_param,  task_param