funasr/models/e2e_asr_contextual_paraformer.py
@@ -233,7 +233,7 @@ stats["loss"] = torch.clone(loss.detach()) # force_gatherable: to-device and to-tensor if scalar for DataParallel if self.length_normalized_loss: batch_size = (text_lengths + self.predictor_bias).sum().type_as(batch_size) batch_size = int((text_lengths + self.predictor_bias).sum()) loss, stats, weight = force_gatherable((loss, stats, batch_size), loss.device) return loss, stats, weight