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/*
* Copyright (C) 2019 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
// This file tests that various abnormal uses of ANeuralNetworks*_free() don't crash.
//
// Limitation: It doesn't set various combinations of properties on objects before
// freeing those objects.
#include "NeuralNetworks.h"
#include <gtest/gtest.h>
#include <vector>
namespace {
ANeuralNetworksModel* createUnfinishedModel() {
ANeuralNetworksModel* model = nullptr;
EXPECT_EQ(ANeuralNetworksModel_create(&model), ANEURALNETWORKS_NO_ERROR);
uint32_t dimensions[] = {1};
ANeuralNetworksOperandType type = {
.type = ANEURALNETWORKS_TENSOR_FLOAT32, .dimensionCount = 1, .dimensions = dimensions};
EXPECT_EQ(ANeuralNetworksModel_addOperand(model, &type), ANEURALNETWORKS_NO_ERROR);
EXPECT_EQ(ANeuralNetworksModel_addOperand(model, &type), ANEURALNETWORKS_NO_ERROR);
const uint32_t inList[]{0};
const uint32_t outList[]{1};
EXPECT_EQ(
ANeuralNetworksModel_addOperation(model, ANEURALNETWORKS_FLOOR, 1, inList, 1, outList),
ANEURALNETWORKS_NO_ERROR);
EXPECT_EQ(ANeuralNetworksModel_identifyInputsAndOutputs(model, 1, inList, 1, outList),
ANEURALNETWORKS_NO_ERROR);
return model;
}
ANeuralNetworksModel* createFinishedModel() {
ANeuralNetworksModel* const model = createUnfinishedModel();
EXPECT_EQ(ANeuralNetworksModel_finish(model), ANEURALNETWORKS_NO_ERROR);
return model;
}
std::vector<ANeuralNetworksDevice*> createDeviceList() {
std::vector<ANeuralNetworksDevice*> devices;
uint32_t numDevices = 0;
EXPECT_EQ(ANeuralNetworks_getDeviceCount(&numDevices), ANEURALNETWORKS_NO_ERROR);
for (uint32_t devIndex = 0; devIndex < numDevices; ++devIndex) {
ANeuralNetworksDevice* device = nullptr;
const int getDeviceStatus = ANeuralNetworks_getDevice(devIndex, &device);
EXPECT_EQ(getDeviceStatus, ANEURALNETWORKS_NO_ERROR);
if (getDeviceStatus == ANEURALNETWORKS_NO_ERROR) {
devices.push_back(device);
}
}
return devices;
}
TEST(Free, Null) {
ANeuralNetworksBurst_free(nullptr);
ANeuralNetworksCompilation_free(nullptr);
ANeuralNetworksEvent_free(nullptr);
ANeuralNetworksExecution_free(nullptr);
ANeuralNetworksMemory_free(nullptr);
ANeuralNetworksModel_free(nullptr);
}
TEST(Free, UnfinishedModel) {
ANeuralNetworksModel* const model = createUnfinishedModel();
ANeuralNetworksModel_free(model);
}
TEST(Free, UnfinishedCompilation) {
ANeuralNetworksModel* const model = createFinishedModel();
ANeuralNetworksCompilation* compilation = nullptr;
ASSERT_EQ(ANeuralNetworksCompilation_create(model, &compilation), ANEURALNETWORKS_NO_ERROR);
ANeuralNetworksCompilation_free(compilation);
ANeuralNetworksModel_free(model);
}
TEST(Free, UnfinishedCompilationForDevices) {
ANeuralNetworksModel* const model = createFinishedModel();
const auto devices = createDeviceList();
ANeuralNetworksCompilation* compilation = nullptr;
ASSERT_EQ(ANeuralNetworksCompilation_createForDevices(model, devices.data(), devices.size(),
&compilation),
ANEURALNETWORKS_NO_ERROR);
ANeuralNetworksCompilation_free(compilation);
ANeuralNetworksModel_free(model);
}
TEST(Free, UnscheduledExecution) {
ANeuralNetworksModel* const model = createFinishedModel();
ANeuralNetworksCompilation* compilation = nullptr;
ASSERT_EQ(ANeuralNetworksCompilation_create(model, &compilation), ANEURALNETWORKS_NO_ERROR);
ASSERT_EQ(ANeuralNetworksCompilation_finish(compilation), ANEURALNETWORKS_NO_ERROR);
ANeuralNetworksExecution* execution = nullptr;
ASSERT_EQ(ANeuralNetworksExecution_create(compilation, &execution), ANEURALNETWORKS_NO_ERROR);
ANeuralNetworksExecution_free(execution);
ANeuralNetworksCompilation_free(compilation);
ANeuralNetworksModel_free(model);
}
} // namespace
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