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67 lines
1.8 KiB
67 lines
1.8 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.ops import operations as P
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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class OpNetWrapper(nn.Cell):
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def __init__(self, op):
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super(OpNetWrapper, self).__init__()
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self.op = op
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def construct(self, *inputs):
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return self.op(*inputs)
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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_sign_float32():
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op = P.Sign()
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op_wrapper = OpNetWrapper(op)
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input_x = Tensor(np.array([[2.0, 0.0, -1.0]]).astype(np.float32))
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outputs = op_wrapper(input_x)
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print(outputs)
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assert np.allclose(outputs.asnumpy(), [[1., 0., -1.]])
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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_sign_int32():
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op = P.Sign()
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op_wrapper = OpNetWrapper(op)
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input_x = Tensor(np.array([[20, 0, -10]]).astype(np.int32))
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outputs = op_wrapper(input_x)
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print(outputs)
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assert np.allclose(outputs.asnumpy(), [[1, 0, -1]])
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if __name__ == '__main__':
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test_sign_float32()
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test_sign_int32()
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