code: def fprop_np(self, data_np):
      
      if not self.calibrated:
        raise ValueError(
            "DkNN needs to be calibrated by calling DkNNModel.calibrate method once before inferring.")
      data_activations = self.get_activations(data_np)
      _, knns_labels = self.find_train_knns(data_activations)
      knns_not_in_class = self.nonconformity(knns_labels)
      _, _, creds = self.preds_conf_cred(knns_not_in_class)
      return creds
docs: Performs a forward pass through the DkNN on an numpy array of data.