class_docstr: This class matches the question with one of the templates
  to extract entity substrings and define which relations
  corresponds to the question
class_docstr_tok: ["This","class","matches","the","question","with","one","of","the","templates","to","extract","entity","substrings","and","define","which","relations","corresponds","to","the","question"]
docstr: Args:
      load_path: path to folder with file with templates
      templates_filename: file with templates
      **kwargs:
docstr_tok: ["Args",":","load_path",":","path","to","folder","with","file","with","templates","templates_filename",":","file","with","templates","*","*","kwargs",":"]
code: def __init__(
      self,
      load_path: str,
      templates_filename: str,
      num_processors: int = None,
      **kwargs,
  ) -> None:
      """
  
      Args:
          load_path: path to folder with file with templates
          templates_filename: file with templates
          **kwargs:
      """
      super().__init__(save_path=None, load_path=load_path)
      self.templates_filename = templates_filename
      self.num_processors = (
          mp.cpu_count() if num_processors == None else num_processors
      )
      self.pool = mp.Pool(self.num_processors)
      self.load()
  
file_path: DeepPavlov/deeppavlov/models/kbqa/template_matcher.py
imports: import functools
  import json
  import multiprocessing
  import re
  from logging import getLogger
  from typing import Any, Tuple, List, Union
  from deeppavlov.core.common.registry import register
  from deeppavlov.core.models.serializable import Serializable
label_desc: Use image node_id 1 to create a new TemplateMatcher object from inherited base classes: Serializable with example: obj = TemplateMatcher(load_path, templates_filename, num_processors)