code: def n_unique_words(doc_or_tokens: types.DocOrTokens) -> int:
      """
      Compute the number of *unique* words in a document.
  
      Args:
          doc_or_tokens: If a spaCy ``Doc``, non-punctuation tokens (words) are extracted;
              if an iterable of spaCy ``Token`` s, all non-punct elements are used.
      """
      words = utils.get_words(doc_or_tokens)
      # NOTE: this stdlib solution is slower than itertoolz for docs with ~250+ words
      # so let's take a small hit on short docs for the sake of big wins on long docs
      # return len({word.lower for word in words})
      return itertoolz.count(
          itertoolz.unique(word.lower for word in words)
      )
  
imports: from __future__ import annotations
  import functools
  import logging
  import math
  from typing import Optional
  import spacy.pipeline
  from cytoolz import itertoolz
  from spacy.tokens import Doc
  from ..None import types
  from .None import utils
label_desc: Use image node_id 3 for calling a global function with example usage: n_unique_words(doc_or_tokens) and returns: itertoolz