class_docstr: Binary loss for ASV Spoofing.
code: def __init__(
      self,
      weight: float = 1.0,
      enc_dim: int = 128,
      s: float = 20,
      m: float = 0.5,
  ):
      super(ASVSpoofAMSoftmaxLoss).__init__()
      self.weight = weight
      self.enc_dim = enc_dim
      self.s = s
      self.m = m
      self.centers = torch.nn.Parameter(torch.randn(2, enc_dim))
      self.sigmoid = torch.nn.Sigmoid()
      self.loss = torch.nn.BCELoss(reduction="mean")
  
imports: import torch
  from espnet2.asvspoof.loss.abs_loss import AbsASVSpoofLoss
  from espnet.nets.pytorch_backend.nets_utils import to_device
label_desc: Use image node_id 1 to create a new ASVSpoofAMSoftmaxLoss object from inherited base classes: AbsASVSpoofLoss with example: obj = ASVSpoofAMSoftmaxLoss(weight, enc_dim, s, m)