1# Copyright 2020-2021 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 24class Net(nn.Cell): 25 def __init__(self): 26 super(Net, self).__init__() 27 self.select = P.Select() 28 29 def construct(self, cond_op, input_x, input_y): 30 return self.select(cond_op, input_x, input_y) 31 32 33@pytest.mark.level0 34@pytest.mark.platform_x86_gpu_training 35@pytest.mark.env_onecard 36def test_select(): 37 context.set_context(mode=context.GRAPH_MODE, device_target="GPU") 38 select = Net() 39 cond = np.array([[True, False], [True, False]]).astype(np.bool) 40 x = np.array([[1.2, 1], [1, 0]]).astype(np.float32) 41 y = np.array([[1, 2], [3, 4.0]]).astype(np.float32) 42 output = select(Tensor(cond), Tensor(x), Tensor(y)) 43 expect = [[1.2, 2], [1, 4.0]] 44 error = np.ones(shape=[2, 2]) * 1.0e-6 45 diff = output.asnumpy() - expect 46 assert np.all(diff < error) 47 assert np.all(-diff < error) 48 49 context.set_context(mode=context.GRAPH_MODE, device_target="GPU") 50 x = np.array([[1, 0], [1, 0]]).astype(np.bool) 51 y = np.array([[0, 0], [1, 1]]).astype(np.bool) 52 output = select(Tensor(cond), Tensor(x), Tensor(y)) 53 expect = np.array([[1, 0], [1, 1]]).astype(np.bool) 54 assert np.all(output.asnumpy() == expect) 55 56 context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU") 57 x = np.array([[1, 0], [1, 0]]).astype(np.bool) 58 y = np.array([[0, 0], [1, 1]]).astype(np.bool) 59 output = select(Tensor(cond), Tensor(x), Tensor(y)) 60 expect = np.array([[1, 0], [1, 1]]).astype(np.bool) 61 assert np.all(output.asnumpy() == expect) 62