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/*
* Copyright (C) 2018 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.
*/
#include <android-base/scopeguard.h>
#include <gtest/gtest.h>
#include "GeneratedTestUtils.h"
#include "HalInterfaces.h"
#include "Memory.h"
#include "MemoryUtils.h"
#include "ModelBuilder.h"
#include "TestNeuralNetworksWrapper.h"
#include "Utils.h"
namespace android::nn::compliance_test {
using namespace hal;
using namespace test_helper;
using HidlModel = V1_3::Model;
using WrapperModel = test_wrapper::Model;
using WrapperOperandType = test_wrapper::OperandType;
using WrapperType = test_wrapper::Type;
// Tag for the compilance tests
class ComplianceTest : public ::testing::Test {};
// Creates a HIDL model from a wrapper model.
static HidlModel createHidlModel(const WrapperModel& wrapperModel) {
auto modelBuilder = reinterpret_cast<const ModelBuilder*>(wrapperModel.getHandle());
EXPECT_TRUE(modelBuilder->isFinished());
EXPECT_TRUE(modelBuilder->isValid());
return modelBuilder->makeHidlModel();
}
static void testAvailableSinceV1_3(const WrapperModel& wrapperModel) {
HidlModel hidlModel = createHidlModel(wrapperModel);
ASSERT_FALSE(compliantWithV1_2(hidlModel));
ASSERT_FALSE(compliantWithV1_1(hidlModel));
ASSERT_FALSE(compliantWithV1_0(hidlModel));
}
static void testAvailableSinceV1_2(const WrapperModel& wrapperModel) {
HidlModel hidlModel = createHidlModel(wrapperModel);
ASSERT_TRUE(compliantWithV1_2(hidlModel));
ASSERT_FALSE(compliantWithV1_1(hidlModel));
ASSERT_FALSE(compliantWithV1_0(hidlModel));
}
static void testAvailableSinceV1_1(const WrapperModel& wrapperModel) {
HidlModel hidlModel = createHidlModel(wrapperModel);
ASSERT_TRUE(compliantWithV1_2(hidlModel));
ASSERT_TRUE(compliantWithV1_1(hidlModel));
ASSERT_FALSE(compliantWithV1_0(hidlModel));
}
static void testAvailableSinceV1_0(const WrapperModel& wrapperModel) {
HidlModel hidlModel = createHidlModel(wrapperModel);
ASSERT_TRUE(compliantWithV1_2(hidlModel));
ASSERT_TRUE(compliantWithV1_1(hidlModel));
ASSERT_TRUE(compliantWithV1_0(hidlModel));
}
static void testAvailableSinceV1_2(const Request& request) {
ASSERT_FALSE(compliantWithV1_0(request));
ASSERT_TRUE(compliantWithV1_2(request));
}
static void testAvailableSinceV1_3(const Request& request) {
ASSERT_FALSE(compliantWithV1_0(request));
ASSERT_FALSE(compliantWithV1_2(request));
}
static const WrapperOperandType kTypeTensorFloat(WrapperType::TENSOR_FLOAT32, {1});
static const WrapperOperandType kTypeTensorFloatRank0(WrapperType::TENSOR_FLOAT32, {});
static const WrapperOperandType kTypeInt32(WrapperType::INT32, {});
const int32_t kNoActivation = ANEURALNETWORKS_FUSED_NONE;
TEST_F(ComplianceTest, Rank0TensorModelInput) {
// A simple ADD operation: op1 ADD op2 = op3, with op1 and op2 of rank 0.
WrapperModel model;
auto op1 = model.addOperand(&kTypeTensorFloatRank0);
auto op2 = model.addOperand(&kTypeTensorFloatRank0);
auto op3 = model.addOperand(&kTypeTensorFloat);
auto act = model.addConstantOperand(&kTypeInt32, kNoActivation);
model.addOperation(ANEURALNETWORKS_ADD, {op1, op2, act}, {op3});
model.identifyInputsAndOutputs({op1, op2}, {op3});
ASSERT_TRUE(model.isValid());
model.finish();
testAvailableSinceV1_2(model);
}
TEST_F(ComplianceTest, Rank0TensorModelOutput) {
// A simple ADD operation: op1 ADD op2 = op3, with op3 of rank 0.
WrapperModel model;
auto op1 = model.addOperand(&kTypeTensorFloat);
auto op2 = model.addOperand(&kTypeTensorFloat);
auto op3 = model.addOperand(&kTypeTensorFloatRank0);
auto act = model.addConstantOperand(&kTypeInt32, kNoActivation);
model.addOperation(ANEURALNETWORKS_ADD, {op1, op2, act}, {op3});
model.identifyInputsAndOutputs({op1, op2}, {op3});
ASSERT_TRUE(model.isValid());
model.finish();
testAvailableSinceV1_2(model);
}
TEST_F(ComplianceTest, Rank0TensorTemporaryVariable) {
// Two ADD operations: op1 ADD op2 = op3, op3 ADD op4 = op5, with op3 of rank 0.
WrapperModel model;
auto op1 = model.addOperand(&kTypeTensorFloat);
auto op2 = model.addOperand(&kTypeTensorFloat);
auto op3 = model.addOperand(&kTypeTensorFloatRank0);
auto op4 = model.addOperand(&kTypeTensorFloat);
auto op5 = model.addOperand(&kTypeTensorFloat);
auto act = model.addConstantOperand(&kTypeInt32, kNoActivation);
model.addOperation(ANEURALNETWORKS_ADD, {op1, op2, act}, {op3});
model.addOperation(ANEURALNETWORKS_ADD, {op3, op4, act}, {op5});
model.identifyInputsAndOutputs({op1, op2, op4}, {op5});
ASSERT_TRUE(model.isValid());
model.finish();
testAvailableSinceV1_2(model);
}
// Hardware buffers are an Android concept, which aren't necessarily
// available on other platforms such as ChromeOS, which also build NNAPI.
#if defined(__ANDROID__)
TEST_F(ComplianceTest, HardwareBufferModel) {
const size_t memorySize = 20;
AHardwareBuffer_Desc desc{
.width = memorySize,
.height = 1,
.layers = 1,
.format = AHARDWAREBUFFER_FORMAT_BLOB,
.usage = AHARDWAREBUFFER_USAGE_CPU_READ_OFTEN | AHARDWAREBUFFER_USAGE_CPU_WRITE_OFTEN,
};
AHardwareBuffer* buffer = nullptr;
ASSERT_EQ(AHardwareBuffer_allocate(&desc, &buffer), 0);
auto allocateGuard =
android::base::make_scope_guard([buffer]() { AHardwareBuffer_release(buffer); });
test_wrapper::Memory memory(buffer);
ASSERT_TRUE(memory.isValid());
// A simple ADD operation: op1 ADD op2 = op3, with op2 using a const hardware buffer.
WrapperModel model;
auto op1 = model.addOperand(&kTypeTensorFloat);
auto op2 = model.addOperand(&kTypeTensorFloat);
auto op3 = model.addOperand(&kTypeTensorFloat);
auto act = model.addConstantOperand(&kTypeInt32, kNoActivation);
model.setOperandValueFromMemory(op2, &memory, 0, sizeof(float));
model.addOperation(ANEURALNETWORKS_ADD, {op1, op2, act}, {op3});
model.identifyInputsAndOutputs({op1}, {op3});
ASSERT_TRUE(model.isValid());
model.finish();
testAvailableSinceV1_2(model);
}
TEST_F(ComplianceTest, HardwareBufferRequest) {
const auto [n, ahwb] = MemoryRuntimeAHWB::create(1024);
ASSERT_EQ(n, ANEURALNETWORKS_NO_ERROR);
Request::MemoryPool sharedMemoryPool, ahwbMemoryPool = ahwb->getMemoryPool();
sharedMemoryPool.hidlMemory(allocateSharedMemory(1024));
ASSERT_TRUE(sharedMemoryPool.hidlMemory().valid());
ASSERT_TRUE(ahwbMemoryPool.hidlMemory().valid());
// AHardwareBuffer as input.
testAvailableSinceV1_2(Request{
.inputs = {{.hasNoValue = false, .location = {.poolIndex = 0}, .dimensions = {}}},
.outputs = {{.hasNoValue = false, .location = {.poolIndex = 1}, .dimensions = {}}},
.pools = {ahwbMemoryPool, sharedMemoryPool},
});
// AHardwareBuffer as output.
testAvailableSinceV1_2(Request{
.inputs = {{.hasNoValue = false, .location = {.poolIndex = 0}, .dimensions = {}}},
.outputs = {{.hasNoValue = false, .location = {.poolIndex = 1}, .dimensions = {}}},
.pools = {sharedMemoryPool, ahwbMemoryPool},
});
}
#endif
TEST_F(ComplianceTest, DeviceMemory) {
Request::MemoryPool sharedMemoryPool, deviceMemoryPool;
sharedMemoryPool.hidlMemory(allocateSharedMemory(1024));
ASSERT_TRUE(sharedMemoryPool.hidlMemory().valid());
deviceMemoryPool.token(1);
// Device memory as input.
testAvailableSinceV1_3(Request{
.inputs = {{.hasNoValue = false, .location = {.poolIndex = 0}, .dimensions = {}}},
.outputs = {{.hasNoValue = false, .location = {.poolIndex = 1}, .dimensions = {}}},
.pools = {deviceMemoryPool, sharedMemoryPool},
});
// Device memory as output.
testAvailableSinceV1_3(Request{
.inputs = {{.hasNoValue = false, .location = {.poolIndex = 0}, .dimensions = {}}},
.outputs = {{.hasNoValue = false, .location = {.poolIndex = 1}, .dimensions = {}}},
.pools = {sharedMemoryPool, deviceMemoryPool},
});
}
class GeneratedComplianceTest : public generated_tests::GeneratedTestBase {};
TEST_P(GeneratedComplianceTest, Test) {
generated_tests::GeneratedModel model;
generated_tests::createModel(testModel, &model);
ASSERT_TRUE(model.isValid());
model.finish();
switch (testModel.minSupportedVersion) {
case TestHalVersion::V1_0:
testAvailableSinceV1_0(model);
break;
case TestHalVersion::V1_1:
testAvailableSinceV1_1(model);
break;
case TestHalVersion::V1_2:
testAvailableSinceV1_2(model);
break;
case TestHalVersion::V1_3:
testAvailableSinceV1_3(model);
break;
case TestHalVersion::UNKNOWN:
FAIL();
}
}
INSTANTIATE_GENERATED_TEST(GeneratedComplianceTest, [](const TestModel& testModel) {
return !testModel.expectFailure && testModel.minSupportedVersion != TestHalVersion::UNKNOWN;
});
} // namespace android::nn::compliance_test
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