class_docstr: A set of functions used to augment data.
  
  Typical usage: ::
      >>> import nltk
      >>> nltk.download('punkt')
      >>> nltk.download('wordnet')
      >>> nltk.download('averaged_perceptron_tagger')
      >>> from textaugment import Wordnet
      >>> t = Wordnet(v=True,n=True,p=0.5)
      >>> t.augment('I love school')
      i adore school
docstr: A method to initialize parameters
  
  :type random_state: int
  :param random_state: seed
  :type v: bool
  :param v: Verb, default is True
  :type n: bool
  :param n: Noun
  :type runs: int
  :param runs: Number of repetition on single text
  :type p: float, optional
  :param p: The probability of success of an individual trial. (0.1<p<1.0), default is 0.5
  :rtype:   None
  :return:  Constructer do not return.
code: def __init__(self, **kwargs):
      """
      A method to initialize parameters
  
      :type random_state: int
      :param random_state: seed
      :type v: bool
      :param v: Verb, default is True
      :type n: bool
      :param n: Noun
      :type runs: int
      :param runs: Number of repetition on single text
      :type p: float, optional
      :param p: The probability of success of an individual trial. (0.1<p<1.0), default is 0.5
      :rtype:   None
      :return:  Constructer do not return.
      """
  
      # Set random state
      if "random_state" in kwargs:
          self.random_state = kwargs["random_state"]
          if isinstance(self.random_state, int):
              np.random.seed(self.random_state)
          else:
              raise TypeError(
                  "random_state must have type int, float, str, bytes, or bytearray"
              )
  
      # Set verb to be default if no values given
      try:
          if "v" not in kwargs and "n" not in kwargs:
              kwargs["v"] = True
              kwargs["n"] = False
          elif "v" in kwargs and "n" not in kwargs:
              kwargs["v"] = True
              kwargs["n"] = False
          elif "v" not in kwargs and "n" in kwargs:
              kwargs["n"] = True
              kwargs["v"] = False
          if "runs" not in kwargs:
              kwargs["runs"] = 1
  
      except KeyError:
          raise
  
      try:
          if "p" in kwargs:
              if type(kwargs["p"]) is not float:
                  raise TypeError(
                      "p represent probability of success and must be a float from 0.1 to 0.9. E.g p=0.5"
                  )
              elif type(kwargs["p"]) is float:
                  self.p = kwargs["p"]
          else:
              kwargs["p"] = 0.5  # Set default value
      except KeyError:
          raise
  
      self.p = kwargs["p"]
      self.v = kwargs["v"]
      self.n = kwargs["n"]
      self.runs = kwargs["runs"]
  
file_path: textaugment/textaugment/wordnet.py
imports: import numpy
  import nltk
  from itertools import chain
  from nltk.corpus import wordnet
label_desc: Use image node_id 1 to create a new Wordnet object  with example: obj = Wordnet()