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/*
* Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
*
* 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 __NNFW_RUA_SHIM_H__
#define __NNFW_RUA_SHIM_H__
#include <rua/Anchor.h>
//
// Memory
//
inline int ANeuralNetworksMemory_createFromFd(size_t size, int protect, int fd, size_t offset,
ANeuralNetworksMemory **memory)
{
return rua::Anchor::get()->memory()->createFromFd(size, protect, fd, offset, memory);
}
inline void ANeuralNetworksMemory_free(ANeuralNetworksMemory *memory)
{
return rua::Anchor::get()->memory()->free(memory);
}
//
// Event
//
inline int ANeuralNetworksEvent_wait(ANeuralNetworksEvent *event)
{
return rua::Anchor::get()->event()->wait(event);
}
inline void ANeuralNetworksEvent_free(ANeuralNetworksEvent *event)
{
return rua::Anchor::get()->event()->free(event);
}
//
// Model
//
inline int ANeuralNetworksModel_create(ANeuralNetworksModel **model)
{
return rua::Anchor::get()->model()->create(model);
}
inline int ANeuralNetworksModel_addOperand(ANeuralNetworksModel *model,
const ANeuralNetworksOperandType *type)
{
return rua::Anchor::get()->model()->addOperand(model, type);
}
inline int ANeuralNetworksModel_setOperandValue(ANeuralNetworksModel *model, int32_t index,
const void *buffer, size_t length)
{
return rua::Anchor::get()->model()->setOperandValue(model, index, buffer, length);
}
inline int ANeuralNetworksModel_setOperandValueFromMemory(ANeuralNetworksModel *model,
int32_t index,
const ANeuralNetworksMemory *memory,
size_t offset, size_t length)
{
return rua::Anchor::get()->model()->setOperandValueFromMemory(model, index, memory, offset,
length);
}
inline int ANeuralNetworksModel_addOperation(ANeuralNetworksModel *model,
ANeuralNetworksOperationType type, uint32_t inputCount,
const uint32_t *inputs, uint32_t outputCount,
const uint32_t *outputs)
{
return rua::Anchor::get()->model()->addOperation(model, type, inputCount, inputs, outputCount,
outputs);
}
inline int ANeuralNetworksModel_identifyInputsAndOutputs(ANeuralNetworksModel *model,
uint32_t inputCount,
const uint32_t *inputs,
uint32_t outputCount,
const uint32_t *outputs)
{
return rua::Anchor::get()->model()->identifyInputsAndOutputs(model, inputCount, inputs,
outputCount, outputs);
}
inline int ANeuralNetworksModel_relaxComputationFloat32toFloat16(ANeuralNetworksModel *model,
bool allow)
{
return rua::Anchor::get()->model()->relaxComputationFloat32toFloat16(model, allow);
}
inline int ANeuralNetworksModel_finish(ANeuralNetworksModel *model)
{
return rua::Anchor::get()->model()->finish(model);
}
inline void ANeuralNetworksModel_free(ANeuralNetworksModel *model)
{
return rua::Anchor::get()->model()->free(model);
}
//
// Compilation
//
inline int ANeuralNetworksCompilation_create(ANeuralNetworksModel *model,
ANeuralNetworksCompilation **compilation)
{
return rua::Anchor::get()->compilation()->create(model, compilation);
}
inline int ANeuralNetworksCompilation_setPreference(ANeuralNetworksCompilation *compilation,
int32_t preference)
{
return rua::Anchor::get()->compilation()->setPreference(compilation, preference);
}
inline int ANeuralNetworksCompilation_finish(ANeuralNetworksCompilation *compilation)
{
return rua::Anchor::get()->compilation()->finish(compilation);
}
inline void ANeuralNetworksCompilation_free(ANeuralNetworksCompilation *compilation)
{
return rua::Anchor::get()->compilation()->free(compilation);
}
//
// Execution
//
inline int ANeuralNetworksExecution_create(ANeuralNetworksCompilation *compilation,
ANeuralNetworksExecution **execution)
{
return rua::Anchor::get()->execution()->create(compilation, execution);
}
inline int ANeuralNetworksExecution_setInput(ANeuralNetworksExecution *execution, int32_t index,
const ANeuralNetworksOperandType *type,
const void *buffer, size_t length)
{
return rua::Anchor::get()->execution()->setInput(execution, index, type, buffer, length);
}
inline int ANeuralNetworksExecution_setInputFromMemory(ANeuralNetworksExecution *execution,
int32_t index,
const ANeuralNetworksOperandType *type,
const ANeuralNetworksMemory *memory,
size_t offset, size_t length)
{
return rua::Anchor::get()->execution()->setInputFromMemory(execution, index, type, memory, offset,
length);
}
inline int ANeuralNetworksExecution_setOutput(ANeuralNetworksExecution *execution, int32_t index,
const ANeuralNetworksOperandType *type, void *buffer,
size_t length)
{
return rua::Anchor::get()->execution()->setOutput(execution, index, type, buffer, length);
}
inline int ANeuralNetworksExecution_setOutputFromMemory(ANeuralNetworksExecution *execution,
int32_t index,
const ANeuralNetworksOperandType *type,
const ANeuralNetworksMemory *memory,
size_t offset, size_t length)
{
return rua::Anchor::get()->execution()->setOutputFromMemory(execution, index, type, memory,
offset, length);
}
inline int ANeuralNetworksExecution_startCompute(ANeuralNetworksExecution *execution,
ANeuralNetworksEvent **event)
{
return rua::Anchor::get()->execution()->startCompute(execution, event);
}
inline void ANeuralNetworksExecution_free(ANeuralNetworksExecution *execution)
{
return rua::Anchor::get()->execution()->free(execution);
}
#endif // __NNFW_RUA_SHIM_H__
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