funasr/models/predictor/cif.py
@@ -544,9 +544,8 @@ token_num_int = torch.max(token_num).type(torch.int32).item() acoustic_embeds = acoustic_embeds[:, :token_num_int, :] return acoustic_embeds, token_num, alphas, cif_peak, token_num2 def get_upsample_timestamp(self, hidden, target_label=None, mask=None, ignore_id=-1, mask_chunk_predictor=None, target_label_length=None, token_num=None): def get_upsample_timestamp(self, hidden, mask=None, token_num=None): h = hidden b = hidden.shape[0] context = h.transpose(1, 2)
