code: def predict_next_word(self, sentence):
      dy.renew_cg()
      init_state = self.builder.initial_state()
      state = init_state
      for cw in sentence:
          # assume word is already a word-id
          x_t = self.lookup[int(cw)]
          state = state.add_input(x_t)
      y_t = state.output()
      r_t = self.bias + (self.R * y_t)
      prob = dy.softmax(r_t)
      return prob
  
file_path: dynet/examples/rnnlm/rnnlm.py
imports: import dynet
  import time
  import random
  from collections import defaultdict
  from itertools import count
  import argparse
  import sys
  import util
label_desc: Use image node_id 5 for calling the RNNLanguageModel obj's underlying member method code with example usage: obj.predict_next_word(sentence) and returns: prob