1# Copyright 2021 Huawei Technologies Co., Ltd 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================ 15 16import numpy as np 17import pytest 18 19import mindspore.context as context 20import mindspore.nn as nn 21from mindspore import Tensor 22from mindspore.ops import operations as P 23 24context.set_context(mode=context.GRAPH_MODE, device_target='CPU') 25 26 27class Netnan(nn.Cell): 28 def __init__(self): 29 super(Netnan, self).__init__() 30 self.isnan = P.IsNan() 31 32 def construct(self, x): 33 return self.isnan(x) 34 35 36x1 = np.array([[1.2, 2, np.nan, 88]]).astype(np.float32) 37x2 = np.array([[np.inf, 1, 88.0, 0]]).astype(np.float32) 38x3 = np.array([[1, 2], [3, 4], [5.0, 88.0]]).astype(np.float32) 39 40 41@pytest.mark.level0 42@pytest.mark.platform_x86_cpu 43@pytest.mark.env_onecard 44def test_nan(): 45 ms_isnan = Netnan() 46 output1 = ms_isnan(Tensor(x1)) 47 expect1 = [[False, False, True, False]] 48 assert (output1.asnumpy() == expect1).all() 49 50 output2 = ms_isnan(Tensor(x2)) 51 expect2 = [[False, False, False, False]] 52 assert (output2.asnumpy() == expect2).all() 53 54 output3 = ms_isnan(Tensor(x3)) 55 expect3 = [[False, False], [False, False], [False, False]] 56 assert (output3.asnumpy() == expect3).all() 57