code: def test_model_N_S_setter(backend_default):
      # weight initialization
      init = Constant(0.08)
  
      # model initialization
      layers = [
          Recurrent(150, init, activation=Logistic()),
          Affine(100, init, bias=init, activation=Rectlin()),
      ]
  
      model = Model(layers=layers)
      model.set_batch_size(20)
      model.set_seq_len(10)
  
file_path: neon/tests/test_model.py
imports: from builtins import zip
  import numpy
  import os
  from neon.backends import gen_backend
  from neon.data import ArrayIterator, MNIST, PTB
  from neon.initializers import Gaussian, Constant
  from neon.layers import GeneralizedCost, Affine, DeepBiRNN, DeepBiLSTM, LSTM, GRU, Dropout, Conv, Pooling, Sequential, MergeMultistream, Recurrent, RecurrentMean
  from neon.models import Model
  from neon.optimizers import GradientDescentMomentum
  from neon.transforms import Rectlin, Logistic, CrossEntropyBinary
  from utils import allclose_with_out
  from neon import NervanaObject
label_desc: Use image node_id 2 for calling a global function with example usage: test_model_N_S_setter(backend_default) without return types