code: def one_hot(
      text,
      n,
      filters='!"#$%&()*+,-./:;<=>?@[\\]^_`{|}~\t\n',
      lower=True,
      split=" ",
      analyzer=None,
  ):
      """One-hot encodes a text into a list of word indexes of size n.
  
      This is a wrapper to the `hashing_trick` function using `hash` as the
      hashing function; unicity of word to index mapping non-guaranteed.
  
      # Arguments
          text: Input text (string).
          n: int. Size of vocabulary.
          filters: list (or concatenation) of characters to filter out, such as
              punctuation. Default: ``!"#$%&()*+,-./:;<=>?@[\\]^_`{|}~\\t\\n``,
              includes basic punctuation, tabs, and newlines.
          lower: boolean. Whether to set the text to lowercase.
          split: str. Separator for word splitting.
          analyzer: function. Custom analyzer to split the text
  
      # Returns
          List of integers in [1, n]. Each integer encodes a word
          (unicity non-guaranteed).
      """
      return hashing_trick(
          text,
          n,
          hash_function=hash,
          filters=filters,
          lower=lower,
          split=split,
          analyzer=analyzer,
      )
  
imports: import json
  import warnings
  from collections import OrderedDict, defaultdict
  from hashlib import md5
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: one_hot(text, n, filters, lower, split, analyzer) and returns: hashing_trick