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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.
*/
#define LOG_TAG "neuralnetworks_hidl_hal_test"
#include "VtsHalNeuralnetworks.h"
namespace android::hardware::neuralnetworks::V1_1::vts::functional {
using V1_0::DeviceStatus;
using V1_0::ErrorStatus;
// create device test
TEST_P(NeuralnetworksHidlTest, CreateDevice) {}
// status test
TEST_P(NeuralnetworksHidlTest, StatusTest) {
Return<DeviceStatus> status = kDevice->getStatus();
ASSERT_TRUE(status.isOk());
EXPECT_EQ(DeviceStatus::AVAILABLE, static_cast<DeviceStatus>(status));
}
// initialization
TEST_P(NeuralnetworksHidlTest, GetCapabilitiesTest) {
Return<void> ret =
kDevice->getCapabilities_1_1([](ErrorStatus status, const Capabilities& capabilities) {
EXPECT_EQ(ErrorStatus::NONE, status);
EXPECT_LT(0.0f, capabilities.float32Performance.execTime);
EXPECT_LT(0.0f, capabilities.float32Performance.powerUsage);
EXPECT_LT(0.0f, capabilities.quantized8Performance.execTime);
EXPECT_LT(0.0f, capabilities.quantized8Performance.powerUsage);
EXPECT_LT(0.0f, capabilities.relaxedFloat32toFloat16Performance.execTime);
EXPECT_LT(0.0f, capabilities.relaxedFloat32toFloat16Performance.powerUsage);
});
EXPECT_TRUE(ret.isOk());
}
} // namespace android::hardware::neuralnetworks::V1_1::vts::functional