1# Copyright 2019 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 24 25class NetOnesLike(nn.Cell): 26 def __init__(self): 27 super(NetOnesLike, self).__init__() 28 self.ones_like = P.OnesLike() 29 30 def construct(self, x): 31 return self.ones_like(x) 32 33 34@pytest.mark.level0 35@pytest.mark.platform_x86_cpu 36@pytest.mark.env_onecard 37def test_OnesLike(): 38 x0_np = np.random.uniform(-2, 2, (2, 3, 4, 4)).astype(np.float32) 39 x1_np = np.random.uniform(-2, 2, 1).astype(np.float32) 40 41 x0 = Tensor(x0_np) 42 x1 = Tensor(x1_np) 43 44 context.set_context(mode=context.GRAPH_MODE, device_target="CPU") 45 ones_like = NetOnesLike() 46 output0 = ones_like(x0) 47 expect0 = np.ones_like(x0_np) 48 diff0 = output0.asnumpy() - expect0 49 error0 = np.ones(shape=expect0.shape) * 1.0e-5 50 assert np.all(diff0 < error0) 51 assert output0.shape == expect0.shape 52 53 output1 = ones_like(x1) 54 expect1 = np.ones_like(x1_np) 55 diff1 = output1.asnumpy() - expect1 56 error1 = np.ones(shape=expect1.shape) * 1.0e-5 57 assert np.all(diff1 < error1) 58 assert output1.shape == expect1.shape 59