code: def test_rnn_cells():
      check_rnn_forward(
          gluon.rnn.Conv1DLSTMCell((5, 7), 10, (3,), (3,)),
          mx.np.ones((8, 3, 5, 7)),
      )
      check_rnn_forward(
          gluon.rnn.Conv1DRNNCell((5, 7), 10, (3,), (3,)),
          mx.np.ones((8, 3, 5, 7)),
      )
      check_rnn_forward(
          gluon.rnn.Conv1DGRUCell((5, 7), 10, (3,), (3,)),
          mx.np.ones((8, 3, 5, 7)),
      )
  
      net = mx.gluon.rnn.SequentialRNNCell()
      net.add(gluon.rnn.Conv1DLSTMCell((5, 7), 10, (3,), (3,)))
      net.add(gluon.rnn.Conv1DRNNCell((10, 5), 11, (3,), (3,)))
      net.add(gluon.rnn.Conv1DGRUCell((11, 3), 12, (3,), (3,)))
      check_rnn_forward(net, mx.np.ones((8, 3, 5, 7)))
  
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 33 for calling a global function with example usage: test_rnn_cells() without return types