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42 lines
1.4 KiB
42 lines
1.4 KiB
5 years ago
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# 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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from mindspore.common.tensor import Tensor
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from mindspore.common import dtype as mstype
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import mindspore.context as context
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from mindspore.ops import operations as P
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import mindspore.nn as nn
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from mindspore.common import ms_function
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@ms_function
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def t1_while(x, y, z):
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y = y + 4
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while x < y:
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x = x + 1
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x = x + 3
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return x
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def test_net():
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context.set_context(mode=context.GRAPH_MODE,device_target="Ascend")
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context.set_context(enable_task_sink=True)
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c1 = Tensor([2], mstype.int32)
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c2 = Tensor([14], mstype.int32)
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c3 = Tensor([1], mstype.int32)
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expect = Tensor([21], mstype.int32)
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ret = t1_while(c1, c2, c3)
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assert (ret == expect)
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if __name__ == "__main__":
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test_net()
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