code: def check_short_utt(ins, size):
      """Check if the utterance is too short for subsampling."""
      if isinstance(ins, Conv1dSubsampling1) and size < 5:
          return True, 5
      if isinstance(ins, Conv1dSubsampling2) and size < 5:
          return True, 5
      if isinstance(ins, Conv1dSubsampling3) and size < 7:
          return True, 7
      if isinstance(ins, Conv2dSubsampling1) and size < 5:
          return True, 5
      if isinstance(ins, Conv2dSubsampling2) and size < 7:
          return True, 7
      if isinstance(ins, Conv2dSubsampling) and size < 7:
          return True, 7
      if isinstance(ins, Conv2dSubsampling6) and size < 11:
          return True, 11
      if isinstance(ins, Conv2dSubsampling8) and size < 15:
          return True, 15
      return False, -1
  
imports: import torch
  from espnet.nets.pytorch_backend.transformer.embedding import PositionalEncoding
label_desc: Use image node_id 1 for calling a global function with example usage: check_short_utt(ins, size) and returns: False,  unknown, True,  int, True,  int, True,  int, True,  int, True,  int, True,  int, True,  int, True,  int