1# Copyright 2020 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 OpNetWrapper(nn.Cell): 28 def __init__(self, op): 29 super(OpNetWrapper, self).__init__() 30 self.op = op 31 32 def construct(self, *inputs): 33 return self.op(*inputs) 34 35 36@pytest.mark.level0 37@pytest.mark.platform_x86_cpu 38@pytest.mark.env_onecard 39def test_notequal_int(): 40 op = P.NotEqual() 41 op_wrapper = OpNetWrapper(op) 42 43 input_x = Tensor(np.array([1, 2, 3]).astype(np.int32)) 44 input_y = Tensor(np.array([11, 2, 13]).astype(np.int32)) 45 outputs = op_wrapper(input_x, input_y) 46 47 print(outputs) 48 assert np.allclose(outputs.asnumpy(), (True, False, True)) 49 50 51@pytest.mark.level0 52@pytest.mark.platform_x86_cpu 53@pytest.mark.env_onecard 54def test_notequal_float(): 55 op = P.NotEqual() 56 op_wrapper = OpNetWrapper(op) 57 58 input_x = Tensor(np.array([1, 2, 3]).astype(np.float32)) 59 input_y = Tensor(np.array([-1, 0, 3]).astype(np.float32)) 60 outputs = op_wrapper(input_x, input_y) 61 62 print(outputs) 63 assert np.allclose(outputs.asnumpy(), (True, True, False)) 64 65 66if __name__ == '__main__': 67 test_notequal_int() 68 test_notequal_float() 69