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79 lines
2.5 KiB
79 lines
2.5 KiB
# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import numpy as np
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import pytest
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore.common import dtype as mstype
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from mindspore.ops import operations as P
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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class Net2I(nn.Cell):
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def __init__(self):
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super(Net2I, self).__init__()
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self.addn = P.AddN()
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def construct(self, x, y):
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return self.addn((x, y))
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_net_2Input():
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x = np.arange(2 * 3 * 2).reshape(2, 3, 2).astype(np.float32)
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y = np.arange(2 * 3 * 2).reshape(2, 3, 2).astype(np.float32)
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addn = Net2I()
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output = addn(Tensor(x, mstype.float32), Tensor(y, mstype.float32))
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print("output:\n", output)
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expect_result = [[[0., 2.],
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[4., 6.],
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[8., 10.]],
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[[12., 14.],
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[16., 18.],
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[20., 22.]]]
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assert (output.asnumpy() == expect_result).all()
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class Net3I(nn.Cell):
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def __init__(self):
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super(Net3I, self).__init__()
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self.addn = P.AddN()
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def construct(self, x, y, z):
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return self.addn((x, y, z))
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_net_3Input():
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x = np.arange(2 * 3).reshape(2, 3).astype(np.float32)
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y = np.arange(2 * 3).reshape(2, 3).astype(np.float32)
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z = np.arange(2 * 3).reshape(2, 3).astype(np.float32)
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addn = Net3I()
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output = addn(Tensor(x, mstype.float32), Tensor(y, mstype.float32), Tensor(z, mstype.float32))
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print("output:\n", output)
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expect_result = [[0., 3., 6.],
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[9., 12., 15]]
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assert (output.asnumpy() == expect_result).all()
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if __name__ == '__main__':
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test_net_2Input()
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test_net_3Input()
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