adapted pcm to 8k

雾聪

2023-12-13 de87e1d180d214e1f49682d2b5fb7c9d2c89ae7e

 funasr/models/e2e_uni_asr.py

@@ -442,7 +442,7 @@
        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 + 1).sum().type_as(batch_size)
            batch_size = int((text_lengths + 1).sum())
        loss, stats, weight = force_gatherable((loss, stats, batch_size), loss.device)
        return loss, stats, weight