class_docstr: This class parses probabilities of tokens to be a token from the entity substring.
docstr: This method makes a list of tags from a list of probas for tags
  Args:
      tokens: text tokens list
      probas: probabilities for tokens to belong to particular tags
  Returns:
      list of tags for tokens
      list of probabilities of these tags
docstr_tok: ["This","method","makes","a","list","of","tags","from","a","list","of","probas","for","tags","Args",":","tokens",":","text","tokens","list","probas",":","probabilities","for","tokens","to","belong","to","particular","tags","Returns",":","list","of","tags","for","tokens","list","of","probabilities","of","these","tags"]
code: def tags_from_probas(
      self, tokens: List[str], probas: np.array
  ) -> Tuple[List[Union[str, List[str]]], List[Any]]:
      """
      This method makes a list of tags from a list of probas for tags
      Args:
          tokens: text tokens list
          probas: probabilities for tokens to belong to particular tags
      Returns:
          list of tags for tokens
          list of probabilities of these tags
      """
      tags = []
      tag_probas = []
      for token, proba in zip(tokens, probas):
          if proba[0] < self.thres_proba:
              tag_num = np.argmax(proba[1:]) + 1
          else:
              tag_num = 0
          tags.append(self.tags[tag_num])
          tag_probas.append(proba[tag_num])
  
      return tags, tag_probas
  
imports: import re
  from collections import defaultdict
  from logging import getLogger
  from string import punctuation
  from typing import List, Tuple, Union, Any
  import numpy
  from nltk.corpus import stopwords
  from deeppavlov.core.commands.utils import expand_path
  from deeppavlov.core.common.registry import register
  from deeppavlov.core.models.component import Component
label_desc: Use image node_id 3 for calling the EntityDetectionParser obj's underlying member method code with example usage: obj.tags_from_probas(tokens, probas) and returns: tags,  tag_probas