forked from OSSInnovation/mindspore
46 lines
1.4 KiB
Python
46 lines
1.4 KiB
Python
# 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 mindspore.context as context
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import mindspore.nn as nn
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from mindspore.ops import operations as P
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from mindspore import Tensor
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from mindspore.train.serialization import export
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
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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, x_, y_):
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return self.add(x_, y_)
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x = np.ones(4).astype(np.float32)
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y = np.ones(4).astype(np.float32)
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def export_net():
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add = Net()
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output = add(Tensor(x), Tensor(y))
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export(add, Tensor(x), Tensor(y), file_name='tensor_add.mindir', file_format='MINDIR')
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print(x)
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print(y)
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print(output.asnumpy())
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if __name__ == "__main__":
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export_net()
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