code: def __init__(
      self,
      model,
      LAYERS,
      INPUT_DIM,
      HIDDEN_DIM,
      VOCAB_SIZE,
      builder=dy.SimpleRNNBuilder,
  ):
      self.builder = builder(LAYERS, INPUT_DIM, HIDDEN_DIM, model)
  
      self.lookup = model.add_lookup_parameters((VOCAB_SIZE, INPUT_DIM))
      self.R = model.add_parameters((VOCAB_SIZE, HIDDEN_DIM))
      self.bias = model.add_parameters((VOCAB_SIZE))
  
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 1 to create a new RNNLanguageModel object  with example: obj = RNNLanguageModel(model, LAYERS, INPUT_DIM, HIDDEN_DIM, VOCAB_SIZE, builder)