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/*
* Copyright (c) 2018 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.
*/
/**
* @file Sinks.h
* @brief This file contains TensorSink class
* @ingroup COM_AI_RUNTIME
*/
#ifndef __INTERNAL_SINKS_H__
#define __INTERNAL_SINKS_H__
#include "internal/Sink.h"
// TODO Extract TensorSink into TensorSink.h
//
// TensorSink
//
#include "internal/Swizzle.h"
#include "internal/nnapi/tensor/View.h"
#include "internal/arm_compute/tensor/View.h"
#include "misc/tensor/IndexIterator.h"
/**
* @brief Class to store NN model output data for general-shaped tensors.
* This is for pulling data to internal tensor from other tensor.
* @tparam T Type of the data elements
*/
template <typename T> class TensorSink final : public Sink
{
public:
/**
* @brief Construct a TensorSink object
*
* @param[in] shape general-shaped tensor dimensions
* @param[in] base Base pointer of the actual data
* @param[in] size Size of the data
*/
TensorSink(const nnfw::misc::tensor::Shape &shape, T *base, const size_t size)
: _shape{shape}, _base{base}, _size{size}
{
// DO NOTHING
}
public:
/**
* @brief Pull the data into the internal structure
* @param[in] tensor The tensor which contains source data
* @return N/A
*/
void pull(::arm_compute::ITensor &tensor) const override
{
const ::internal::arm_compute::tensor::View<T> from{&tensor};
::internal::nnapi::tensor::View<T> into{_shape, _base, _size};
using ::nnfw::misc::tensor::iterate;
using ::nnfw::misc::tensor::Index;
const uint32_t rank = _shape.rank();
::nnfw::misc::tensor::iterate(_shape) << [&](const Index &raw) {
Index permuted(raw.rank());
for (uint32_t axis = 0; axis < rank; ++axis)
{
permuted.at(ToARMComputeAxis(rank, axis).value()) = raw.at(axis);
}
const auto value = from.at(permuted);
into.at(raw) = value;
};
}
private:
const nnfw::misc::tensor::Shape _shape;
private:
T *const _base;
const size_t _size;
};
#endif // __INTERNAL_SINKS_H__
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