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52 lines
1.8 KiB
52 lines
1.8 KiB
# Copyright 2019 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 pytest
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from mindspore import Tensor
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from mindspore.ops import operations as P
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import mindspore.nn as nn
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import numpy as np
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import mindspore.context as context
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from mindspore.common import dtype as mstype
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from mindspore.common.initializer import initializer
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from mindspore.common.parameter import Parameter
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
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class NetArgmax(nn.Cell):
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def __init__( self):
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super(NetArgmax, self).__init__()
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self.argmax = P.Argmax(output_type=mstype.int32)
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x = Tensor(np.array([[1., 20., 5.],
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[67., 8., 9.],
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[130., 24., 15.]]).astype(np.float32))
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self.x = Parameter(initializer(x, x.shape()), name ='x')
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def construct(self):
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return self.argmax(self.x)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_argmax():
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Argmax = NetArgmax()
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output = Argmax()
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print("================================")
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expect = np.array([1,0,0]).astype(np.float32)
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print(output)
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assert (output.asnumpy() == expect).all()
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