code: def get_eval_preproc_spec(
      *,
      input_size: int,
      num_instances: int,
      max_queries: int,
      max_query_length: int = 16,
  ):
      """Constructs training preprocess string."""
      return (
          f"resize_with_pad(size={input_size})"
          f"|canonicalize_text_labels"
          f"|crop_or_pad({input_size}, {num_instances})"
          f"|crop_or_pad_meta_data({num_instances}, {num_instances})"
          f"|single_to_multi_label(max_num_labels={num_instances})"
          f"|add_query_set(lower=True, max_queries={max_queries},"
          f" include_negatives=True)"
          f"|clip_tokenize_queries(max_token_len={max_query_length})"
      )
  
label_desc: Use image node_id 2 for calling a global function with example usage: get_eval_preproc_spec() and returns: str, input_size, str, input_size, str, num_instances, str, num_instances, str, num_instances, str, num_instances, str, max_queries, str, max_query_length, str