code: def __init__(
      self,
      win_length: int = 512,
      hop_length: int = 128,
      center: bool = True,
  ):
      assert check_argument_types()
      super().__init__()
  
      self.win_length = win_length
      self.hop_length = hop_length
      self.center = center
  
file_path: espnet/espnet2/layers/label_aggregation.py
imports: from typing import Optional, Tuple
  import torch
  from typeguard import check_argument_types
  from espnet.nets.pytorch_backend.nets_utils import make_pad_mask
label_desc: Use image node_id 1 to create a new LabelAggregate object from inherited base classes: torch.nn with example: obj = LabelAggregate(win_length, hop_length, center)