class_docstr: Glove Preprocessor to split tokens that can be passed into glove embeddings 
docstr: Initialize the GLovePreprocessor
  
  :param count_thresh: the minimum number of times a word has to appear
  in a sentence to be counted as part of the vocabulary
  :type int
  :param token_cutoff: the maximum number of tokens a sentence can have
  :type token_cutoff: int
code: def __init__(self, count_threshold: int, token_cutoff: int):
      """Initialize the GLovePreprocessor
  
      :param count_thresh: the minimum number of times a word has to appear
      in a sentence to be counted as part of the vocabulary
      :type int
      :param token_cutoff: the maximum number of tokens a sentence can have
      :type token_cutoff: int
      """
      self.count_threshold = count_threshold
      self.token_cutoff = token_cutoff
  
file_path: interpret-text/python/interpret_text/experimental/common/preprocessor/glove_preprocessor.py
imports: import numpy
  import pandas
  from typing import Any, Iterable, List
  from interpret_text.experimental.common.base_explainer import BaseTextPreprocessor
label_desc: Use image node_id 1 to create a new GlovePreprocessor object from inherited base classes: BaseTextPreprocessor with example: obj = GlovePreprocessor(count_threshold, token_cutoff)