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/*
* Copyright (c) 2020 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 "TensorBuilder.h"
#include <util/logging.h>
#include <cassert>
namespace onert
{
namespace backend
{
namespace controlflow
{
TensorBuilder::TensorBuilder()
: _tensor_reg{new cpu_common::TensorRegistry()}, _user_tensor_reg{new UserTensorRegistry()},
_static_tensor_mgr{new cpu_common::StaticTensorManager(_tensor_reg)},
_dynamic_tensor_mgr{new DynamicTensorManager(_tensor_reg, _user_tensor_reg)}
{
/* empty */
}
void TensorBuilder::registerTensorInfo(const ir::OperandIndex &ind, const ir::OperandInfo &info,
ir::Layout backend_layout)
{
_tensor_info_map.emplace(ind, info);
_tensor_layout_map.insert({ind, backend_layout});
if (info.isDynamic())
{
_dynamic_tensor_mgr->buildTensor(ind, info, _tensor_layout_map[ind]);
}
else
{
_static_tensor_mgr->buildTensor(ind, info, _tensor_layout_map[ind], info.isConstant());
}
}
void TensorBuilder::notifyFirstUse(const ir::OperandIndex &ind)
{
assert(_tensor_info_map.find(ind) != _tensor_info_map.end());
const auto tensor_info = _tensor_info_map.at(ind);
if (!at(ind)->is_dynamic())
{
const auto size = tensor_info.total_size();
_static_tensor_mgr->claimPlan(ind, size);
}
}
void TensorBuilder::notifyLastUse(const ir::OperandIndex &ind)
{
if (!at(ind)->is_dynamic())
{
_static_tensor_mgr->releasePlan(ind);
}
}
bool TensorBuilder::isRegistered(const ir::OperandIndex &ind) const
{
return _tensor_info_map.find(ind) != _tensor_info_map.end();
}
void TensorBuilder::prepare(void)
{
_static_tensor_mgr->allocateConsts();
_static_tensor_mgr->allocateNonconsts();
}
void TensorBuilder::allocate()
{
// NOTE For now nothing to do. Allocation is done in prepare stage, which is not appropriate
// This is because CPU kernels require `ITensor`s to be allocated before Kernel Generation.
}
std::shared_ptr<ITensor> TensorBuilder::tensorAt(const ir::OperandIndex &ind)
{
// NOTE Find from User Tensor Registry first
// FIXME There may be both user tensor and managed tensor for a `ind` which is a waste
auto user_tensor = _user_tensor_reg->getITensor(ind);
auto tensor = _tensor_reg->getITensor(ind);
if (user_tensor)
{
return user_tensor;
}
else
return tensor;
}
void TensorBuilder::iterate(const IterateFunction &fn) { _static_tensor_mgr->iterate(fn); }
std::shared_ptr<cpu_common::Tensor> TensorBuilder::at(const ir::OperandIndex &ind)
{
return _tensor_reg->getManagedTensor(ind);
}
std::unique_ptr<ITensorManager> TensorBuilder::releaseStaticTensorManager(void)
{
return std::move(_static_tensor_mgr);
}
std::unique_ptr<ITensorManager> TensorBuilder::releaseDynamicTensorManager(void)
{
return std::move(_dynamic_tensor_mgr);
}
void TensorBuilder::setUserTensor(const ir::OperandIndex &ind,
const std::shared_ptr<UserTensor> &tensor)
{
_user_tensor_reg->setManagedTensor(ind, tensor);
}
} // namespace controlflow
} // namespace backend
} // namespace onert
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