class_docstr: Interface to the Stanford Tokenizer
  
  >>> from nltk.tokenize.stanford import StanfordTokenizer
  >>> s = "Good muffins cost $3.88\nin New York.  Please buy me\ntwo of them.\nThanks."
  >>> StanfordTokenizer().tokenize(s) # doctest: +SKIP
  ['Good', 'muffins', 'cost', '$', '3.88', 'in', 'New', 'York', '.', 'Please', 'buy', 'me', 'two', 'of', 'them', '.', 'Thanks', '.']
  >>> s = "The colour of the wall is blue."
  >>> StanfordTokenizer(options={"americanize": True}).tokenize(s) # doctest: +SKIP
  ['The', 'color', 'of', 'the', 'wall', 'is', 'blue', '.']
code: def __init__(
      self,
      path_to_jar=None,
      encoding="utf8",
      options=None,
      verbose=False,
      java_options="-mx1000m",
  ):
      # Raise deprecation warning.
      warnings.warn(
          str(
              "\nThe StanfordTokenizer will "
              "be deprecated in version 3.2.5.\n"
              "Please use \033[91mnltk.parse.corenlp.CoreNLPParser\033[0m instead.'"
          ),
          DeprecationWarning,
          stacklevel=2,
      )
  
      self._stanford_jar = find_jar(
          self._JAR,
          path_to_jar,
          env_vars=("STANFORD_POSTAGGER",),
          searchpath=(),
          url=_stanford_url,
          verbose=verbose,
      )
  
      self._encoding = encoding
      self.java_options = java_options
  
      options = {} if options is None else options
      self._options_cmd = ",".join(
          f"{key}={val}" for key, val in options.items()
      )
  
file_path: nltk/nltk/tokenize/stanford.py
imports: import json
  import os
  import tempfile
  import warnings
  from subprocess import PIPE
  from nltk.internals import _java_options, config_java, find_jar, java
  from nltk.parse.corenlp import CoreNLPParser
  from nltk.tokenize.api import TokenizerI
label_desc: Use image node_id 1 to create a new StanfordTokenizer object from inherited base classes: TokenizerI with example: obj = StanfordTokenizer(path_to_jar, encoding, options, verbose, java_options)