class_docstr: Binary loss for ASV Spoofing.
code: def __init__(
      self,
      weight: float = 1.0,
      enc_dim: int = 128,
      m_real: float = 0.5,
      m_fake: float = 0.2,
      alpha: float = 20.0,
  ):
      super(ASVSpoofOCSoftmaxLoss).__init__()
      self.weight = weight
      self.feat_dim = enc_dim
      self.m_real = m_real
      self.m_fake = m_fake
      self.alpha = alpha
      self.center = torch.nn.Parameter(torch.randn(1, self.feat_dim))
      torch.nn.init.kaiming_uniform_(self.center, 0.25)
      self.softplus = torch.nn.Softplus()
  
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 ASVSpoofOCSoftmaxLoss object from inherited base classes: AbsASVSpoofLoss with example: obj = ASVSpoofOCSoftmaxLoss(weight, enc_dim, m_real, m_fake, alpha)