class_docstr: Binary loss for ASV Spoofing.
docstr: Prediction.
  Args:
      emb (torch.Tensor): encoder embedding output [Batch, T, enc_dim]
docstr_tok: ["Prediction",".","Args",":","emb","(","torch.Tensor",")",":","encoder","embedding","output","[","Batch",",","T",",","enc_dim","]"]
code: def score(self, emb: torch.Tensor):
      """Prediction.
      Args:
          emb (torch.Tensor): encoder embedding output [Batch, T, enc_dim]
      """
      emb = torch.mean(emb, dim=1)
      w = torch.nn.functional.normalize(self.center, p=2, dim=1)
      x = torch.nn.functional.normalize(emb, p=2, dim=1)
  
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 3 for calling the ASVSpoofOCSoftmaxLoss obj's underlying member method code with example usage: obj.score(emb) without return types