class_docstr: discriminator loss for UASR.
code: def __init__(
      self,
      weight: float = 1.0,
      smoothing: float = 0.0,
      smoothing_one_side: str2bool = False,
      reduction: str = "sum",
  ):
      super().__init__()
      assert check_argument_types()
      self.weight = weight
      self.smoothing = smoothing
      self.smoothing_one_sided = smoothing_one_side
      self.reduction = reduction
  
file_path: espnet/espnet2/uasr/loss/discriminator_loss.py
imports: import torch
  import torch.nn.functional
  from typeguard import check_argument_types
  from espnet2.uasr.loss.abs_loss import AbsUASRLoss
  from espnet2.utils.types import str2bool
label_desc: Use image node_id 1 to create a new UASRDiscriminatorLoss object from inherited base classes: AbsUASRLoss with example: obj = UASRDiscriminatorLoss(weight, smoothing, smoothing_one_side, reduction)