code: def sample(self, first=1, nchars=0, stop=-1):
      res = [first]
      dy.renew_cg()
      state = self.builder.initial_state()
  
      R = dy.parameter(self.R)
      bias = dy.parameter(self.bias)
      cw = first
      while True:
          x_t = dy.lookup(self.lookup, cw)
          state = state.add_input(x_t)
          y_t = state.output()
          r_t = bias + (R * y_t)
          ydist = dy.softmax(r_t)
          dist = ydist.vec_value()
          rnd = random.random()
          for i, p in enumerate(dist):
              rnd -= p
              if rnd <= 0:
                  break
          res.append(i)
          cw = i
          if cw == stop:
              break
          if nchars and len(res) > nchars:
              break
      return res
  
file_path: dynet/examples/batching/rnnlm-batch.py
imports: import dynet
  import time
  import random
  import argparse
  from collections import defaultdict
  from itertools import count
  import sys
  import util
label_desc: Use image node_id 3 for calling the RNNLanguageModel obj's underlying member method code with example usage: obj.sample(first, nchars, stop) and returns: res