code: def test_2d_sparse_sequences_value(device_id):
      dev = cntk_device(device_id)
      seq1_data = [[[0, 1, 1], [0, 1, 0]], [[1, 0, 0], [1, 0, 1]]]
      csr_seq1 = _to_csr(seq1_data)
      ndarrayview1 = C.NDArrayView.from_csr(
          csr_seq1, shape=(2, 2, 3), device=C.cpu()
      )
      seq2_data = [[0, 1, 1], [1, 1, 0]]
      csr_seq2 = _to_csr(seq2_data)
      ndarrayview2 = C.NDArrayView.from_csr(
          csr_seq2, shape=(1, 2, 3), device=C.cpu()
      )
  
      x = C.sequence.input_variable((2, 3))
      sequence_value = C.Value.create(
          x, [ndarrayview1, ndarrayview2], device=dev
      )
      assert np.array_equal(
          _to_dense(sequence_value.data),
          [seq1_data, [seq2_data, [[0, 0, 0], [0, 0, 0]]]],
      )
  
imports: import pytest
  import numpy
  import scipy.sparse
  import cntk
  from cntk.ops.tests.ops_test_utils import cntk_device
  from cntk.internal import _value_as_sequence_or_array
  from cntk import asvalue
  from cntk.tests.test_utils import _to_dense, _to_csr
label_desc: Use image node_id 11 for calling a global function with example usage: test_2d_sparse_sequences_value(device_id) without return types