class_docstr: S3Rec is the first work to incorporate self-supervised learning in
  sequential recommendation.
  
  NOTE:
      Under this framework, we need reconstruct the pretraining data,
      which would affect the pre-training speed.
code: def _segment_prediction(self, context, segment_emb):
      context = self.sp_norm(context)
      score = torch.mul(context, segment_emb)  # [B H]
      return torch.sigmoid(torch.sum(score, dim=-1))
  
imports: import random
  import torch
  from torch import nn
  from recbole.model.abstract_recommender import SequentialRecommender
  from recbole.model.layers import TransformerEncoder
  from recbole.model.loss import BPRLoss
label_desc: Use image node_id 6 for calling the S3Rec obj's underlying member method code with example usage: obj._segment_prediction(context, segment_emb) and returns: torch