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- # Copyright 2020 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
- from cus_add3 import CusAdd3
-
- import mindspore.context as context
- import mindspore.nn as nn
- from mindspore import Tensor
-
- context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
-
-
- class Net(nn.Cell):
- """Net definition"""
-
- def __init__(self):
- super(Net, self).__init__()
- self.add3 = CusAdd3(1.0)
-
- def construct(self, input1, input2):
- return self.add3(input1, input2)
-
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_ascend_training
- @pytest.mark.platform_arm_ascend_training
- @pytest.mark.env_onecard
- def test_net():
- input1 = np.array([1.0, 4.0, 9.0]).astype(np.float32)
- input2 = np.array([1.0, 2.0, 3.0]).astype(np.float32)
- add3_net = Net()
- output = add3_net(Tensor(input1), Tensor(input2))
- expect = np.array([3.0, 7.0, 13.0]).astype(np.float32)
- assert (output.asnumpy() == expect).all()
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