code: def top1(self, O, Y, M):
      target_scores = torch.diag(O)
      target_scores = target_scores.reshape(target_scores.shape[0], -1)
      return torch.sum(
          (
              torch.mean(
                  torch.sigmoid(O - target_scores)
                  + torch.sigmoid(O**2),
                  axis=1,
              )
              - torch.sigmoid(target_scores**2) / (M + self.n_sample)
          )
      )
  
imports: from collections import Counter
  import numpy
  import torch
  from torch import nn
  from torch.autograd import Variable
  from torch.optim import Optimizer
  from cornac.utils.common import get_rng
label_desc: Use image node_id 7 for calling the GRU4RecModel obj's underlying member method code with example usage: obj.top1(O, Y, M) and returns: torch