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