  def debug_model(
      config,
      resolved_train_config,
      nlp,
      model: Model,
      *,
      print_settings: Optional[Dict[str, Any]] = None,
  ):
      if not isinstance(model, Model):
          msg.fail(
 
</s> remove     if not hasattr(pipe, "model"):
        msg.fail(
            f"The component '{component}' does not specify an object that holds a Model.",
            exits=1,
        )
    model = pipe.model
    debug_model(config, T, nlp, model, print_settings=print_settings)
 </s> add     debug_model(config, T, nlp, pipe, print_settings=print_settings) </s> remove                     "Could not initialize the model: you'll have to provide a valid train_corpus argument in the config file.",
 </s> add                     "Could not initialize the model: you'll have to provide a valid 'train_corpus' argument in the config file.", </s> remove def get_gradient(goldY, Y, ops):
    return ops.asarray(Y) - ops.asarray(goldY)


def _simulate_gold(element, counter=1):
    if isinstance(element, Iterable):
        for i in range(len(element)):
            element[i] = _simulate_gold(element[i], counter + i)
        return element
    else:
        return 1 / counter


 </s> add  </s> remove                     nlp.initialize(lambda: [Example.from_dict(x, {}) for x in X])
 </s> add                     examples = [Example.from_dict(x, {}) for x in _get_docs()]
                    nlp.initialize(lambda: examples)
    pipe,
  def debug_model(
      config,
      resolved_train_config,
      nlp,
    pipe,
      *,
      print_settings: Optional[Dict[str, Any]] = None,
  ):
      if not isinstance(model, Model):
          msg.fail(
keep keep keep keep replace keep keep keep keep keep
 Fix 'debug model' for transformers + generalize (#7973)

* add overrides to docs

* fix debug model with transformer

* assume training data is set in config 
spacy/cli/debug_model.py