text: Title: How to increase NPairsLoss batch size. 
  Body: This is more of a question:
  
  When using  NPairsLoss, it's creating unique pairs before running the Cross Entropy Loss (just like in the paper). Is there a way to **increase the batch size** by adding more examples for each class? Or will the loss function only keep one example of each class? Are all the negative examples kept? 
  
  For example, can I feed a representation tensor of size N * M * V, where N is the batch size, M the number of different examples for a single class and V the embedding size?