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/*
* Copyright (c) 2021, 2023-2024 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef ACL_SRC_CPU_UTILS_CPUAUXTENSORHANDLER_H
#define ACL_SRC_CPU_UTILS_CPUAUXTENSORHANDLER_H
#include "arm_compute/core/ITensorPack.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/runtime/Tensor.h"
#include "src/common/utils/Log.h"
#include "support/Cast.h"
namespace arm_compute
{
namespace cpu
{
/** Tensor handler to wrap and handle tensor allocations on workspace buffers
*
* @note Important: Despite the impression given by its name, the handler owns, rather than merely points to, the
* underlying tensor memory.
*
* @note About memory handling using bypass_* flags
* The bypass_alloc / bypass_import flags are meant to skip the expensive auxiliary tensor memory allocations or
* imports that are not needed during runtime, e.g. when the handler is not used at all in some branch of execution.
*
* If not handled correctly, these two flags can lead to performance issues (not bypass when needed to), or memory
* bugs (bypass when should not to).
*
* Make sure:
*
* 1. The aux tensor handlers must always be declared at the root level, or the same level as the run/prepare
* methods that potentially use them.
*
* Once the handler is destroyed (e.g. when going out of scope), the memory it owns (returned by the get()
* method) will also be destroyed.
*
* Thus it's important to ensure the handler is always in-scope when it is being used by a operator / kernel.
*
* 2. The handler's bypass_alloc and bypass_import flags should always be inverse of whether the handler is used in
* its surrounding scope by run/prepare. (This usually means being added to some tensor pack)
*
* This ensures we only bypass if and only if the aux tensor is not used by the op / kernel later.
*
*
* So the general usage pattern goes like this:
*
* bool use_aux_tensor = some_condition_about_when_to_use_the_aux_tensor
*
* CpuAuxTensorHandler aux_handler {..., !use_aux_tensor || bypass_alloc / bypass_import ||};
*
* if (use_aux_tensor)
* {
* tensor_pack.add_tensor(aux_handler.get());
* }
* op.run(tensor_pack);
*/
class CpuAuxTensorHandler
{
public:
/** Create a temporary tensor handle, by either important an existing tensor from a tensor pack, or allocating a
* new one.
*
* @param[in] slot_id Slot id of the tensor to be retrieved in the tensor pack
* If no such tensor exists in the tensor pack, a new tensor will be allocated.
* @param[in] info Tensor info containing requested size of the new tensor.
* If requested size is larger than the tensor retrieved from the tensor pack,
* a new tensor will be allocated.
* @param[in,out] pack Tensor pack to retrieve the old tensor. When @p pack_inject is true, the new
* tensor will also be added here.
* @param[in] pack_inject In case of a newly allocated tensor, whether to add this tensor back to the
* @p pack
* @param[in] bypass_alloc Bypass allocation in case of a new tensor
* This is to prevent unnecessary memory operations when the handler object is not
* used
* @param[in] bypass_import Bypass importation in case of a retrieved tensor
* This is to prevent unnecessary memory operations when the handler object is not
* used
*/
CpuAuxTensorHandler(int slot_id,
TensorInfo &info,
ITensorPack &pack,
bool pack_inject = false,
bool bypass_alloc = false,
bool bypass_import = false)
: _tensor()
{
if (info.total_size() == 0)
{
return;
}
_tensor.allocator()->soft_init(info);
ITensor *packed_tensor = utils::cast::polymorphic_downcast<ITensor *>(pack.get_tensor(slot_id));
if ((packed_tensor == nullptr) || (info.total_size() > packed_tensor->info()->total_size()))
{
if (!bypass_alloc)
{
_tensor.allocator()->allocate();
ARM_COMPUTE_LOG_INFO_WITH_FUNCNAME_ACL("Allocating auxiliary tensor");
}
if (pack_inject)
{
pack.add_tensor(slot_id, &_tensor);
_injected_tensor_pack = &pack;
_injected_slot_id = slot_id;
}
}
else
{
if (!bypass_import)
{
_tensor.allocator()->import_memory(packed_tensor->buffer());
}
}
}
/** Create a temporary handle to the original tensor with a new @ref TensorInfo
* This is useful if we want to change a tensor's tensor info at run time without modifying the original tensor
*
* @param[in] info New tensor info to "assign" to @p tensor
* @param[in] tensor Tensor to be assigned a new @ref TensorInfo
* @param[in] bypass_import Bypass importing @p tensor's memory into the handler.
* This is to prevent unnecessary memory operations when the handler object is not used
*/
CpuAuxTensorHandler(TensorInfo &info, const ITensor &tensor, bool bypass_import = false) : _tensor()
{
_tensor.allocator()->soft_init(info);
if (!bypass_import)
{
ARM_COMPUTE_ERROR_ON(tensor.info() == nullptr);
if (info.total_size() <= tensor.info()->total_size())
{
_tensor.allocator()->import_memory(tensor.buffer());
}
}
}
CpuAuxTensorHandler(const CpuAuxTensorHandler &) = delete;
CpuAuxTensorHandler &operator=(const CpuAuxTensorHandler) = delete;
~CpuAuxTensorHandler()
{
if (_injected_tensor_pack)
{
_injected_tensor_pack->remove_tensor(_injected_slot_id);
}
}
ITensor *get()
{
return &_tensor;
}
ITensor *operator()()
{
return &_tensor;
}
private:
Tensor _tensor{};
ITensorPack *_injected_tensor_pack{nullptr};
int _injected_slot_id{TensorType::ACL_UNKNOWN};
};
} // namespace cpu
} // namespace arm_compute
#endif // ACL_SRC_CPU_UTILS_CPUAUXTENSORHANDLER_H
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