add introduction of fst hotwords

雾聪

2024-01-01 f047ff8aa4fb11215a3eb5a425fee77ff72e5dba

 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