| @@ -19,7 +19,6 @@ import mindspore.nn as nn | |||
| from mindspore import Tensor | |||
| from mindspore.ops import operations as P | |||
| context.set_context(mode=context.GRAPH_MODE, device_target="GPU") | |||
| class Net(nn.Cell): | |||
| def __init__(self, _shape): | |||
| @@ -30,6 +29,7 @@ class Net(nn.Cell): | |||
| def construct(self, indices, update): | |||
| return self.scatternd(indices, update, self.shape) | |||
| def scatternd_net(indices, update, _shape, expect): | |||
| scatternd = Net(_shape) | |||
| output = scatternd(Tensor(indices), Tensor(update)) | |||
| @@ -38,13 +38,49 @@ def scatternd_net(indices, update, _shape, expect): | |||
| assert np.all(diff < error) | |||
| assert np.all(-diff < error) | |||
| def scatternd_positive(nptype): | |||
| context.set_context(mode=context.GRAPH_MODE, device_target="GPU") | |||
| arr_indices = np.array([[0, 1], [1, 1], [0, 1], [0, 1], [0, 1]]).astype(np.int32) | |||
| arr_update = np.array([3.2, 1.1, 5.3, -2.2, -1.0]).astype(nptype) | |||
| shape = (2, 2) | |||
| expect = np.array([[0., 5.3], | |||
| [0., 1.1]]).astype(nptype) | |||
| scatternd_net(arr_indices, arr_update, shape, expect) | |||
| def scatternd_negative(nptype): | |||
| context.set_context(mode=context.GRAPH_MODE, device_target="GPU") | |||
| arr_indices = np.array([[1, 0], [1, 1], [1, 0], [1, 0], [1, 0]]).astype(np.int32) | |||
| arr_update = np.array([-13.4, -3.1, 5.1, -12.1, -1.0]).astype(nptype) | |||
| shape = (2, 2) | |||
| expect = np.array([[0., 0.], | |||
| [-21.4, -3.1]]).astype(nptype) | |||
| scatternd_net(arr_indices, arr_update, shape, expect) | |||
| @pytest.mark.level0 | |||
| @pytest.mark.platform_x86_gpu_traning | |||
| @pytest.mark.env_onecard | |||
| def test_scatternd(): | |||
| arr_indices = np.array([[0, 1], [1, 1]]).astype(np.int32) | |||
| arr_update = np.array([3.2, 1.1]).astype(np.float32) | |||
| shape = (2, 2) | |||
| expect = np.array([[0., 3.2], | |||
| [0., 1.1]]) | |||
| scatternd_net(arr_indices, arr_update, shape, expect) | |||
| def test_scatternd_float32(): | |||
| scatternd_positive(np.float32) | |||
| scatternd_negative(np.float32) | |||
| @pytest.mark.level0 | |||
| @pytest.mark.platform_x86_gpu_traning | |||
| @pytest.mark.env_onecard | |||
| def test_scatternd_float16(): | |||
| scatternd_positive(np.float16) | |||
| scatternd_negative(np.float16) | |||
| @pytest.mark.level0 | |||
| @pytest.mark.platform_x86_gpu_traning | |||
| @pytest.mark.env_onecard | |||
| def test_scatternd_int16(): | |||
| scatternd_positive(np.int16) | |||
| scatternd_negative(np.int16) | |||
| @pytest.mark.level0 | |||
| @pytest.mark.platform_x86_gpu_traning | |||
| @pytest.mark.env_onecard | |||
| def test_scatternd_uint8(): | |||
| scatternd_positive(np.uint8) | |||