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- # Copyright 2021 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ============================================================================
-
- import numpy as np
- import pytest
-
- import mindspore.nn as nn
- from mindspore import Tensor
- from mindspore import context
- from mindspore.ops import operations as P
-
- context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
-
-
- class NetSin(nn.Cell):
- def __init__(self):
- super(NetSin, self).__init__()
- self.sin = P.Sin()
-
- def construct(self, x):
- return self.sin(x)
-
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_cpu
- @pytest.mark.env_onecard
- def test_sin():
- np_array = np.array([-1, -0.5, 0, 0.5, 1]).astype('float32')
- input_x = Tensor(np_array)
- net = NetSin()
- output = net(input_x)
- print(output)
- expect = np.sin(np_array)
- assert np.allclose(output.asnumpy(), expect)
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