code: def masked_language_model(vocab, model, mask_prob=0.15):
      
  
      random_words = _RandomWords(vocab)
  
      def mlm_forward(docs, drop=0.0):
          mask, docs = _apply_mask(docs, random_words, mask_prob=mask_prob)
          mask = model.ops.asarray(mask).reshape((mask.shape[0], 1))
          output, backprop = model.begin_update(docs, drop=drop)
  
          def mlm_backward(d_output, sgd=None):
              d_output *= 1 - mask
              return backprop(d_output, sgd=sgd)
  
          return output, mlm_backward
  
      return wrap(mlm_forward, model)
docs: Convert a model into a BERT-style masked language model