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@ -23,6 +23,7 @@ from mindspore.common.api import ms_function
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from mindspore.common.initializer import initializer
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from mindspore.common.parameter import Parameter
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from mindspore.ops import operations as P
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from mindspore.ops.operations import _inner_ops as inner
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context.set_context(device_target='GPU')
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@ -129,3 +130,62 @@ def test_TensorAdd():
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assert (output[1].asnumpy() == expect1).all()
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assert (output[2].asnumpy() == expect2).all()
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assert (output[3].asnumpy() == expect3).all()
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class Tensoradd_d(nn.Cell):
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def __init__(self):
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super(Tensoradd_d, self).__init__()
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self.test_dynamic = inner.GpuConvertToDynamicShape()
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self.add = P.TensorAdd()
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def construct(self, x, y):
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x = self.test_dynamic(x)
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y = self.test_dynamic(y)
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return self.add(x, y)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_TensorAdd_dynamic():
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context.set_context(device_target='GPU', mode=context.GRAPH_MODE)
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net = Tensoradd_d()
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x1 = Tensor(np.arange(3).reshape(3).astype(np.float32))
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y1 = Tensor(np.array([2]).astype(np.float32))
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x2 = Tensor(np.arange(3 * 3 * 3 * 3).reshape(3, 3, 3, 3).astype(np.float32))
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y2 = Tensor(np.arange(3 * 3 * 3 * 3).reshape(3, 3, 3, 3).astype(np.float32))
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expect1 = np.array([2, 3, 4])
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expect2 = np.array(
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[[[[0., 2., 4.],
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[6., 8., 10.],
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[12., 14., 16.]],
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[[18., 20., 22.],
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[24., 26., 28.],
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[30., 32., 34.]],
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[[36., 38., 40.],
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[42., 44., 46.],
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[48., 50., 52.]]],
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[[[54., 56., 58.],
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[60., 62., 64.],
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[66., 68., 70.]],
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[[72., 74., 76.],
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[78., 80., 82.],
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[84., 86., 88.]],
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[[90., 92., 94.],
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[96., 98., 100.],
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[102., 104., 106.]]],
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[[[108., 110., 112.],
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[114., 116., 118.],
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[120., 122., 124.]],
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[[126., 128., 130.],
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[132., 134., 136.],
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[138., 140., 142.]],
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[[144., 146., 148.],
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[150., 152., 154.],
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[156., 158., 160.]]]])
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output1 = net(x1, y1)
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output2 = net(x2, y2)
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assert (output1.asnumpy() == expect1).all()
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assert (output2.asnumpy() == expect2).all()
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