class_docstr: This class provides a wrapper of SpaCy of tokenizer, pos tagger and named entity recognizer
class_docstr_tok: ["This","class","provides","a","wrapper","of","SpaCy","of","tokenizer",",","pos","tagger","and","named","entity","recognizer"]
code: def __init__(self):
      try:
          import spacy  # default english
          from numpy import dot
          from numpy.linalg import norm
  
          self._nlp = spacy.load("en_core_web_sm")
          self._vocab = list(
              set(
                  [
                      w.orth_
                      for w in self._nlp.vocab
                      if w.orth_.islower()
                  ]
              )
          )
          self._cosine = lambda v1, v2: dot(v1, v2) / (
              norm(v1) * norm(v2)
          )
      except Exception as ex:
          print("Error loading spacy: ", ex)
          print("Install SpaCy. https://spacy.io/docs/usage/")
          import sys
  
          sys.exit()
  
imports: from sematch.utility import FileIO
  from nltk.stem import WordNetLemmatizer
  from nltk.corpus import wordnet
  import nltk
  from collections import Counter
  import itertools
  import string
  import re
label_desc: Use image node_id 1 to create a new SpaCyNLP object  with example: obj = SpaCyNLP()