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47 lines
1.4 KiB
47 lines
1.4 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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import mindspore
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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='CPU')
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class SubNet(nn.Cell):
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def __init__(self):
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super(SubNet, self).__init__()
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self.sub = P.Sub()
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def construct(self, x, y):
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return self.sub(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_sub():
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x = np.random.rand(2, 3, 4, 4).astype(np.float32)
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y = np.random.rand(4, 1).astype(np.float32)
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net = SubNet()
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output = net(Tensor(x), Tensor(y, mindspore.float32))
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expect_output = x - y
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assert np.all(output.asnumpy() == expect_output)
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test_sub()
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