1# Copyright 2022 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 as ms 20import mindspore.nn as nn 21import mindspore.ops as ops 22 23 24class Net(nn.Cell): 25 def construct(self, x): 26 output = ops.fliplr(x) 27 return output 28 29 30@pytest.mark.level2 31@pytest.mark.platform_x86_cpu 32@pytest.mark.platform_arm_cpu 33@pytest.mark.platform_x86_gpu_training 34@pytest.mark.platform_arm_ascend_training 35@pytest.mark.platform_x86_ascend_training 36@pytest.mark.env_onecard 37@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE]) 38def test_fliplr_normal(mode): 39 """ 40 Feature: fliplr 41 Description: Verify the result of fliplr 42 Expectation: success 43 """ 44 ms.set_context(mode=mode) 45 net = Net() 46 x = ms.Tensor(np.arange(8).reshape((2, 2, 2))) 47 out = net(x) 48 expect_out = np.array([[[2., 3.], 49 [0., 1.]], 50 [[6., 7.], 51 [4., 5.]]]) 52 assert np.allclose(out.asnumpy(), expect_out) 53