code: def test_gather_implementation_using_one_hot_and_times():
      num_classes = 4
  
      w_init = np.asarray([[0, 1], [2, 3], [4, 5], [6, 7]]).astype(
          np.float32
      )
      w = C.parameter(init=w_init)
  
      x = C.input_variable((2,))
      sparse_one_hot = C.one_hot(x, num_classes, sparse_output=True)
      t = C.times(sparse_one_hot, w)
      indices = np.asarray([[0, 3], [2, 1]], dtype=np.float32)
      result = t.eval({x: indices})
      expected_result = np.asarray(
          [[[0.0, 1.0], [6.0, 7.0]], [[4.0, 5.0], [2.0, 3.0]]]
      )
      assert np.array_equal(result, expected_result)
  
imports: import numpy
  import scipy
  import pytest
  import cntk
  from .ops_test_utils import cntk_device
  from cntk.axis import Axis
  from ..None import constant
  from cntk.tests.test_utils import _to_dense
label_desc: Use image node_id 10 for calling a global function with example usage: test_gather_implementation_using_one_hot_and_times() without return types