code: def reconstruction_metrics(
      original: str, decompressed: str
  ) -> Mapping:
      return {
          # Accuracies
          "exact_match": float(original == decompressed),
          "semantic_similarity": 1
          - semantic_distance(original, decompressed),
          # Errors
          "semantic_distance": semantic_distance(
              original, decompressed
          ),
          "character_error_rate_ignore_case_cap1": min(
              jiwer.cer(original.lower(), decompressed.lower()), 1.0
          ),
          "character_error_rate_ignore_case": jiwer.cer(
              original.lower(), decompressed.lower()
          ),
          "character_error_rate_cap1": min(
              jiwer.cer(original, decompressed), 1.0
          ),
          "character_error_rate": jiwer.cer(original, decompressed),
          "word_error_rate": jiwer.wer(original, decompressed),
          "match_error_rate": jiwer.mer(original, decompressed),
          "word_information_lost": jiwer.wil(original, decompressed),
      }
  
imports: from typing import Mapping
  import jiwer
  import spacy_universal_sentence_encoder
label_desc: Use image node_id 1 for calling a global function with example usage: reconstruction_metrics(original, decompressed) and returns: dict