forked from mindspore-Ecosystem/mindspore
57 lines
1.7 KiB
Python
57 lines
1.7 KiB
Python
# Copyright 2021 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 pytest
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import mindspore.context as context
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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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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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class Netnan(nn.Cell):
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def __init__(self):
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super(Netnan, self).__init__()
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self.isnan = P.IsNan()
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def construct(self, x):
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return self.isnan(x)
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x1 = np.array([[1.2, 2, np.nan, 88]]).astype(np.float32)
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x2 = np.array([[np.inf, 1, 88.0, 0]]).astype(np.float32)
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x3 = np.array([[1, 2], [3, 4], [5.0, 88.0]]).astype(np.float32)
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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_nan():
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ms_isnan = Netnan()
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output1 = ms_isnan(Tensor(x1))
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expect1 = [[False, False, True, False]]
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assert (output1.asnumpy() == expect1).all()
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output2 = ms_isnan(Tensor(x2))
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expect2 = [[False, False, False, False]]
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assert (output2.asnumpy() == expect2).all()
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output3 = ms_isnan(Tensor(x3))
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expect3 = [[False, False], [False, False], [False, False]]
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assert (output3.asnumpy() == expect3).all()
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