      }
      for eg in examples:
          gold = eg.reference
          doc = eg.predicted
          valid_words = [x for x in gold if x is not None]
          data["words"].update(valid_words)
          data["n_words"] += len(valid_words)
          data["n_misaligned_words"] += len(gold) - len(valid_words)
          data["texts"].add(doc.text)
          if len(nlp.vocab.vectors):
 
</s> remove             for word in valid_words:
 </s> add             for word in [t.text for t in doc]: </s> remove         data["n_misaligned_words"] += len(gold) - len(valid_words)
 </s> add         align = eg.alignment
        for token in doc:
            if token.orth_.isspace():
                continue
            if align.x2y.lengths[token.i] != 1:
                data["n_misaligned_words"] += 1
        valid_words = [x.text for x in gold]
      }
      for eg in examples:
          gold = eg.reference
          doc = eg.predicted
        valid_words = [x.text for x in gold]
          data["words"].update(valid_words)
          data["n_words"] += len(valid_words)
          data["n_misaligned_words"] += len(gold) - len(valid_words)
          data["texts"].add(doc.text)
          if len(nlp.vocab.vectors):
keep keep keep keep replace keep keep keep keep keep
 Fix alignment and vector checks in debug data

* Update token alignment check to use Example alignment
* Update missing vector check further related to changes in v3 
spacy/cli/debug_data.py