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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.
*/
#ifndef __NEURUN_UTIL_FEATURE_NHWC_READER_H__
#define __NEURUN_UTIL_FEATURE_NHWC_READER_H__
#include <cassert>
#include "backend/operand/ITensor.h"
#include "misc/feature/Reader.h"
#include "misc/feature/Shape.h"
#include "util/Coordinates.h"
#include "util/Utils.h"
namespace neurun
{
namespace util
{
namespace feature
{
namespace nhwc
{
template <typename T> class Reader final : public nnfw::misc::feature::Reader<T>
{
public:
// Construct for buffer of model inputs
Reader(const ::nnfw::misc::feature::Shape &shape, const T *ptr, size_t len)
: _shape{shape}, _ptr{reinterpret_cast<const uint8_t *>(ptr)}, _len{len}
{
UNUSED_RELEASE(len); // Workaround for unused variable in release mode
assert(shape.N * shape.C * shape.H * shape.W * sizeof(T) == len);
// No padding
_strides.C = sizeof(T);
_strides.W = shape.C * sizeof(T);
_strides.H = shape.C * shape.W * sizeof(T);
_strides.N = shape.C * shape.W * shape.H * sizeof(T);
}
// Construct for backend tensor
Reader(const backend::operand::ITensor *tensor)
: _ptr{tensor->buffer() + tensor->calcOffset({0, 0, 0, 0})}, _len{tensor->total_size()}
{
assert(tensor->layout() == ir::Layout::NHWC);
const auto start_offset = tensor->calcOffset({0, 0, 0, 0});
_strides.C = tensor->dimension(3) == 1 ? 0 : tensor->calcOffset({0, 0, 0, 1}) - start_offset;
_strides.W = tensor->dimension(2) == 1 ? 0 : tensor->calcOffset({0, 0, 1, 0}) - start_offset;
_strides.H = tensor->dimension(1) == 1 ? 0 : tensor->calcOffset({0, 1, 0, 0}) - start_offset;
_strides.N = tensor->dimension(0) == 1 ? 0 : tensor->calcOffset({1, 0, 0, 0}) - start_offset;
_shape.C = tensor->dimension(3);
_shape.W = tensor->dimension(2);
_shape.H = tensor->dimension(1);
_shape.N = tensor->dimension(0);
}
public:
T at(uint32_t row, uint32_t col, uint32_t ch) const override
{
const auto offset = feature_index_to_byte_offset(0, row, col, ch);
const T *ptr = reinterpret_cast<const T *>(_ptr + offset);
return *ptr;
}
T at(uint32_t batch, uint32_t row, uint32_t col, uint32_t ch) const override
{
const auto offset = feature_index_to_byte_offset(batch, row, col, ch);
const T *ptr = reinterpret_cast<const T *>(_ptr + offset);
return *ptr;
}
private:
size_t feature_index_to_byte_offset(uint32_t batch, uint32_t row, uint32_t col, uint32_t ch) const
{
assert(1u * _shape.N > batch); // shape.N > batch
assert(1u * _shape.H > row); // shape.H > row
assert(1u * _shape.W > col); // shape.W > col
assert(1u * _shape.C > ch); // shape.C > ch
uint32_t res = 0;
res += batch * _strides.N;
res += row * _strides.H;
res += col * _strides.W;
res += ch * _strides.C;
return res;
}
private:
// TODO Remove _shape
nnfw::misc::feature::Shape _shape;
using Strides = nnfw::misc::feature::Shape;
Strides _strides;
const uint8_t *_ptr;
size_t _len;
};
} // namespace nhwc
} // namespace feature
} // namespace util
} // namespace neurun
#endif // __NEURUN_UTIL_FEATURE_NHWC_READER_H__
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