code: def cosine_similarity_vec(num_tokens, num_removed_vec):
      """
      Return cosine similarity between a binary vector with all ones
      of length ``num_tokens`` and vectors of the same length with
      ``num_removed_vec`` elements set to zero.
      """
      remaining = -np.array(num_removed_vec) + num_tokens
      return remaining / (
          np.sqrt(num_tokens + 1e-6) * np.sqrt(remaining + 1e-6)
      )
  
imports: from __future__ import absolute_import
  import re
  import math
  from typing import List, Tuple, Union, Optional
  import numpy
  from sklearn.utils import check_random_state
  from eli5.utils import indices_to_bool_mask, vstack
label_desc: Use image node_id 2 for calling a global function with example usage: cosine_similarity_vec(num_tokens, num_removed_vec) and returns: unknown