code: def test_sequence_unpack_with_convolution(device_id, precision):
      dt = PRECISION_TO_TYPE[precision]
      dev = cntk_device(device_id)
  
      x = C.sequence.input((20, 20), dtype=dt)
      y = C.sequence.unpack(x, 0, no_mask_output=True)
      z = C.reshape(y, (3, 20, 20))
      kernel = C.constant(1.0, (4, 3, 3, 3), device=dev)
      t = C.convolution(kernel, z, auto_padding=[False, True, True])
      val = np.random.random((2, 3, 20, 20)).astype(dt)
      result = t.eval({x: val}, device=dev)
      assert np.array_equal(result.shape, (2, 4, 20, 20))
  
imports: from __future__ import division
  import numpy
  import pytest
  import cntk
  from .ops_test_utils import cntk_device
  from cntk.tests.test_utils import _to_dense, _to_csr
  from .ops_test_utils import unittest_helper, _test_unary_op, _test_binary_op, AA, precision, PRECISION_TO_TYPE, cntk_device
  from cntk import Value
  from cntk.axis import Axis
  from cntk.internal import sanitize_dtype_cntk
  from ..None import constant
label_desc: Use image node_id 26 for calling a global function with example usage: test_sequence_unpack_with_convolution(device_id, precision) without return types