code: def test_recurrent_nparams_hid_init_layer():
      # test that you can see layers through hid_init
      l_inp = InputLayer((2, 2, 3))
      l_inp_h = InputLayer((2, 5))
      l_inp_h_de = DenseLayer(l_inp_h, 7)
      l_rec = RecurrentLayer(l_inp, 7, hid_init=l_inp_h_de)
  
      # directly check the layers can be seen through hid_init
      assert lasagne.layers.get_all_layers(l_rec) == [
          l_inp,
          l_inp_h,
          l_inp_h_de,
          l_rec,
      ]
  
      # b, W_hid_to_hid and W_in_to_hid + W + b
      assert (
          len(lasagne.layers.get_all_params(l_rec, trainable=True)) == 5
      )
  
      # b (recurrent) + b (dense)
      assert (
          len(lasagne.layers.get_all_params(l_rec, regularizable=False))
          == 2
      )
  
imports: import pytest
  from lasagne.layers import RecurrentLayer, LSTMLayer, CustomRecurrentLayer
  from lasagne.layers import InputLayer, DenseLayer, GRULayer, Gate, Layer
  from lasagne.layers import helper
  import theano
  import theano.tensor
  import numpy
  import lasagne
  from mock import Mock
label_desc: Use image node_id 6 for calling a global function with example usage: test_recurrent_nparams_hid_init_layer() without return types