funasr/models/predictor/cif.py
@@ -208,7 +208,8 @@ mask_2 = torch.cat([ones_t, mask], dim=1) mask = mask_2 - mask_1 tail_threshold = mask * tail_threshold alphas = torch.cat([alphas, tail_threshold], dim=1) alphas = torch.cat([alphas, zeros_t], dim=1) alphas = torch.add(alphas, tail_threshold) else: tail_threshold = torch.tensor([tail_threshold], dtype=alphas.dtype).to(alphas.device) tail_threshold = torch.reshape(tail_threshold, (1, 1))
