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 20from mindspore import Tensor, nn 21from mindspore.common import dtype as mstype 22 23 24class CaseNet(nn.Cell): 25 def __init__(self): 26 super(CaseNet, self).__init__() 27 self.conv = nn.Conv2d(1, 1, 3) 28 self.relu = nn.ReLU() 29 self.relu1 = nn.ReLU() 30 self.softmax = nn.Softmax() 31 self.layers1 = (self.relu, self.softmax) 32 self.layers2 = (self.conv, self.relu1) 33 34 def construct(self, x, index1, index2): 35 x = self.layers1[index1](x) 36 x = self.layers2[index2](x) 37 return x 38 39 40@pytest.mark.level1 41@pytest.mark.platform_arm_ascend_training 42@pytest.mark.platform_x86_ascend_training 43@pytest.mark.platform_x86_gpu_training 44@pytest.mark.env_onecard 45def test_switch_layer(): 46 context.set_context(mode=context.GRAPH_MODE) 47 net = CaseNet() 48 data = Tensor(np.ones((1, 1, 224, 224)), mstype.float32) 49 idx = Tensor(0, mstype.int32) 50 idx2 = Tensor(-1, mstype.int32) 51 value = net(data, idx, idx2) 52 relu = nn.ReLU() 53 true_value = relu(data) 54 ret = np.allclose(value.asnumpy(), true_value.asnumpy()) 55 assert ret 56