funasr/models/encoder/conformer_encoder.py
@@ -1078,7 +1078,7 @@ limit_size, ) mask = make_source_mask(x_len) mask = make_source_mask(x_len).to(x.device) if self.unified_model_training: chunk_size = self.default_chunk_size + torch.randint(-self.jitter_range, self.jitter_range+1, (1,)).item()
