blob: 30e5578b666db5707e70ba141971a24cf44ddc0f [file] [log] [blame]
/*
* 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.
*/
#ifndef ANDROID_HARDWARE_NEURALNETWORKS_V1_2_GENERATED_TEST_HARNESS_H
#define ANDROID_HARDWARE_NEURALNETWORKS_V1_2_GENERATED_TEST_HARNESS_H
#include <android/hardware/neuralnetworks/1.2/IDevice.h>
#include <android/hardware/neuralnetworks/1.2/IPreparedModel.h>
#include <android/hardware/neuralnetworks/1.2/types.h>
#include <functional>
#include <vector>
#include "TestHarness.h"
namespace android {
namespace hardware {
namespace neuralnetworks {
namespace generated_tests {
using ::test_helper::MixedTypedExample;
void PrepareModel(const sp<V1_2::IDevice>& device, const V1_2::Model& model,
sp<V1_2::IPreparedModel>* preparedModel);
void EvaluatePreparedModel(sp<V1_2::IPreparedModel>& preparedModel,
std::function<bool(int)> is_ignored,
const std::vector<MixedTypedExample>& examples,
bool hasRelaxedFloat32Model, bool testDynamicOutputShape);
void Execute(const sp<V1_2::IDevice>& device, std::function<V1_2::Model(void)> create_model,
std::function<bool(int)> is_ignored, const std::vector<MixedTypedExample>& examples,
bool testDynamicOutputShape = false);
} // namespace generated_tests
} // namespace neuralnetworks
} // namespace hardware
} // namespace android
#endif // ANDROID_HARDWARE_NEURALNETWORKS_V1_2_GENERATED_TEST_HARNESS_H