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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.
- # ============================================================================
- """ test TensorAdd """
- import numpy as np
- import mindspore.nn as nn
- from mindspore import Tensor
- from mindspore.ops import operations as P
-
- class Net(nn.Cell):
- def __init__(self):
- super(Net, self).__init__()
- self.add = P.TensorAdd()
-
- def construct(self, input1, input2):
- return self.add(input1, input2)
-
-
- def test_tensor_add():
- """test_tensor_add"""
- add = P.TensorAdd()
- input1 = Tensor(np.random.rand(1, 3, 4, 4).astype(np.float32))
- input2 = Tensor(np.random.rand(1, 3, 4, 4).astype(np.float32))
- output = add(input1, input2)
- output_np = output.asnumpy()
- input1_np = input1.asnumpy()
- input2_np = input2.asnumpy()
- print(input1_np[0][0][0][0])
- print(input2_np[0][0][0][0])
- print(output_np[0][0][0][0])
- assert isinstance(output_np[0][0][0][0], np.float32)
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