docstr: Calculates the GE2E loss for an input of dimensions (num_speakers, num_utts_per_speaker, dvec_feats)
docstr_tok: ["Calculates","the","GE2E","loss","for","an","input","of","dimensions","(","num_speakers",",","num_utts_per_speaker",",","dvec_feats",")"]
code: def forward(self, x, _label=None):
      """
      Calculates the GE2E loss for an input of dimensions (num_speakers, num_utts_per_speaker, dvec_feats)
      """
  
      assert x.size()[1] >= 2
  
      centroids = torch.mean(x, 1)
      cos_sim_matrix = self.calc_cosine_sim(x, centroids)
      torch.clamp(self.w, 1e-6)
      cos_sim_matrix = self.w * cos_sim_matrix + self.b
      L = self.embed_loss(x, cos_sim_matrix)
      return L.mean()
  
imports: import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 6 for calling the GE2ELoss obj's underlying member method code with example usage: obj.forward(x, _label) and returns: L