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