blob: eef99374e7b9644f4933c3eaa80cfaa621833f5d [file] [log] [blame]
/*
* Copyright (C) 2017 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 "SampleDriverMinimal"
#include <android-base/logging.h>
#include <thread>
#include <vector>
#include "HalInterfaces.h"
#include "NeuralNetworksOEM.h"
#include "SampleDriverPartial.h"
#include "Utils.h"
#include "ValidateHal.h"
namespace android {
namespace nn {
namespace sample_driver {
class SampleDriverMinimal : public SampleDriverPartial {
public:
SampleDriverMinimal() : SampleDriverPartial("nnapi-sample_minimal") {}
hardware::Return<void> getCapabilities_1_3(getCapabilities_1_3_cb cb) override;
private:
std::vector<bool> getSupportedOperationsImpl(const V1_3::Model& model) const override;
};
hardware::Return<void> SampleDriverMinimal::getCapabilities_1_3(getCapabilities_1_3_cb cb) {
android::nn::initVLogMask();
VLOG(DRIVER) << "getCapabilities()";
V1_3::Capabilities capabilities = {
.relaxedFloat32toFloat16PerformanceScalar = {.execTime = 0.4f, .powerUsage = 0.5f},
.relaxedFloat32toFloat16PerformanceTensor = {.execTime = 0.4f, .powerUsage = 0.5f},
.operandPerformance = nonExtensionOperandPerformance<HalVersion::V1_3>({1.0f, 1.0f}),
.ifPerformance = {.execTime = 1.0f, .powerUsage = 1.0f},
.whilePerformance = {.execTime = 1.0f, .powerUsage = 1.0f}};
update(&capabilities.operandPerformance, V1_3::OperandType::TENSOR_FLOAT32,
{.execTime = 0.4f, .powerUsage = 0.5f});
update(&capabilities.operandPerformance, V1_3::OperandType::FLOAT32,
{.execTime = 0.4f, .powerUsage = 0.5f});
cb(V1_3::ErrorStatus::NONE, capabilities);
return hardware::Void();
}
std::vector<bool> SampleDriverMinimal::getSupportedOperationsImpl(const V1_3::Model& model) const {
const size_t count = model.main.operations.size();
std::vector<bool> supported(count);
// Simulate supporting just a few ops
for (size_t i = 0; i < count; i++) {
supported[i] = false;
const V1_3::Operation& operation = model.main.operations[i];
switch (operation.type) {
case V1_3::OperationType::ADD:
case V1_3::OperationType::CONCATENATION:
case V1_3::OperationType::CONV_2D: {
const V1_3::Operand& firstOperand = model.main.operands[operation.inputs[0]];
if (firstOperand.type == V1_3::OperandType::TENSOR_FLOAT32) {
supported[i] = true;
}
break;
}
default:
break;
}
}
return supported;
}
} // namespace sample_driver
} // namespace nn
} // namespace android
using android::sp;
using android::nn::sample_driver::SampleDriverMinimal;
int main() {
sp<SampleDriverMinimal> driver(new SampleDriverMinimal());
return driver->run();
}