diff --git a/egs/librispeech/ASR/conformer_ctc2/decode.py b/egs/librispeech/ASR/conformer_ctc2/decode.py
index 673053c55..3abcf588e 100755
--- a/egs/librispeech/ASR/conformer_ctc2/decode.py
+++ b/egs/librispeech/ASR/conformer_ctc2/decode.py
@@ -241,34 +241,6 @@ def ctc_greedy_search(
     return hyps, scores
 
 
-def make_pad_mask(lengths: torch.Tensor, max_len: int = 0) -> torch.Tensor:
-    """Make mask tensor containing indices of padded part.
-
-    See description of make_non_pad_mask.
-
-    Args:
-        lengths (torch.Tensor): Batch of lengths (B,).
-    Returns:
-        torch.Tensor: Mask tensor containing indices of padded part.
-
-    Examples:
-        >>> lengths = [5, 3, 2]
-        >>> make_pad_mask(lengths)
-        masks = [[0, 0, 0, 0 ,0],
-                 [0, 0, 0, 1, 1],
-                 [0, 0, 1, 1, 1]]
-    """
-    batch_size = lengths.size(0)
-    max_len = max_len if max_len > 0 else lengths.max().item()
-    seq_range = torch.arange(
-        0, max_len, dtype=torch.int64, device=lengths.device
-    )
-    seq_range_expand = seq_range.unsqueeze(0).expand(batch_size, max_len)
-    seq_length_expand = lengths.unsqueeze(-1)
-    mask = seq_range_expand >= seq_length_expand
-    return mask
-
-
 def remove_duplicates_and_blank(hyp: List[int]) -> List[int]:
     new_hyp: List[int] = []
     cur = 0