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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.
*/
#include "ExecutorBase.h"
#include "util/logging.h"
namespace neurun
{
namespace exec
{
ExecutorBase::ExecutorBase(const std::shared_ptr<const model::Model> &model,
std::unique_ptr<model::Subgraphs> subgraphs,
const std::shared_ptr<compiler::OperandContext> &operand_context,
std::unique_ptr<graph::LowerInfoMap> lower_info,
std::unique_ptr<backend::TensorManagerSet> tensor_mgrs)
: _observers(), _model{model}, _subgraphs{std::move(subgraphs)},
_operand_context{operand_context}, _lower_info{std::move(lower_info)},
_tensor_mgrs{std::move(tensor_mgrs)}, _mutex()
{
// DO NOTHING
}
std::unique_ptr<ISource> ExecutorBase::source(const model::IOIndex &index,
const model::TypeInfo &type, const void *buffer,
size_t length)
{
using ::neurun::model::DataType;
switch (type.type())
{
case DataType::FLOAT32:
return source<float>(index, buffer, length);
case DataType::INT32:
return source<int32_t>(index, buffer, length);
case DataType::UINT32:
return source<uint32_t>(index, buffer, length);
case DataType::BOOL8:
case DataType::QUANT8_ASYMM:
return source<uint8_t>(index, buffer, length);
default:
throw std::runtime_error("Not supported yet");
}
}
std::unique_ptr<ISink> ExecutorBase::sink(const model::IOIndex &index, const model::TypeInfo &type,
void *buffer, size_t length)
{
using ::neurun::model::DataType;
switch (type.type())
{
case DataType::FLOAT32:
return sink<float>(index, buffer, length);
case DataType::INT32:
return sink<int32_t>(index, buffer, length);
case DataType::UINT32:
return sink<uint32_t>(index, buffer, length);
case DataType::BOOL8:
case DataType::QUANT8_ASYMM:
return sink<uint8_t>(index, buffer, length);
default:
throw std::runtime_error("Not supported yet");
}
}
void ExecutorBase::execute(const IODescription &desc)
{
// For thread-safe, use mutex
// TODO: if all used backends on this executor are thread-safe,
// do not need to use mutex (otherwise, use mutex)
std::lock_guard<std::mutex> lock(_mutex);
std::vector<std::unique_ptr<ISource>> sources{_model->inputs.size()};
std::vector<std::unique_ptr<ISink>> sinks{_model->outputs.size()};
// Set input(s)
for (uint32_t n = 0; n < _model->inputs.size(); ++n)
{
model::IOIndex input_index{n};
model::OperandIndex index{_model->inputs.at(input_index)};
if (desc.inputs.at(n) == nullptr)
{
// Optional input
continue;
}
const auto operand_li = _lower_info->operand.at(index).get();
if (operand_li->def_factors().empty())
{
// This input is not used (i.e. constant, EX. reshape's axis)
continue;
}
const auto &input = *desc.inputs.at(n);
sources.at(n) = source(input_index, input.info.typeInfo(), input.buffer, input.size);
auto setter = [&](::neurun::backend::operand::ITensor &tensor) { sources.at(n)->push(tensor); };
auto object = _operand_context->at(index);
object->access(setter);
}
executeImpl();
// Get output(s)
for (uint32_t n = 0; n < _model->outputs.size(); ++n)
{
neurun::model::IOIndex output_index{n};
// Optional output
if (desc.outputs.at(n) == nullptr)
{
continue;
}
const auto &output = *desc.outputs.at(n);
sinks.at(n) = sink(output_index, output.info.typeInfo(), output.buffer, output.size);
auto getter = [&](::neurun::backend::operand::ITensor &tensor) { sinks.at(n)->pull(tensor); };
::neurun::model::OperandIndex index{_model->outputs.at(output_index)};
auto object = _operand_context->at(index);
object->access(getter);
}
}
} // namespace exec
} // namespace neurun
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