code: def test_sequential_rnn_cells(
      seq_rnn_type, determinism, merged_inputs, hybridize, merge_outputs
  ):
      net = gluon.rnn.SequentialRNNCell()
      net.add(gluon.rnn.LSTMCell(10, input_size=5))
      net.add(gluon.rnn.RNNCell(10, input_size=10))
      net.add(gluon.rnn.GRUCell(10, input_size=10))
      if not determinism:
          net.add(gluon.rnn.DropoutCell(0.5))
      check_rnn_forward_backward(
          net, merged_inputs, hybridize, merge_outputs, determinism
      )
  
imports: import mxnet
  from mxnet import gluon, np
  import numpy
  import copy
  from functools import partial
  from numpy.testing import assert_allclose
  from mxnet.gluon.utils import split_rnn_params
  import pytest
  from mxnet.test_utils import almost_equal, assert_almost_equal, default_device
  from common import assert_raises_cudnn_not_satisfied, retry
label_desc: Use image node_id 17 for calling a global function with example usage: test_sequential_rnn_cells(seq_rnn_type, determinism, merged_inputs, hybridize, merge_outputs) without return types