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/*
* Copyright (c) 2017 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.
*/
#pragma once
#include <cstdint>
#include <cstdlib>
#include "alloc.hpp"
#include "gemm.hpp"
#include "profiler.hpp"
#include "utils.hpp"
#include "shims.hpp"
#include "winograd_gemm.hpp"
#include "transforms.hpp"
#ifndef ALLOC_ALIGN
#define ALLOC_ALIGN 64
#endif // ALLOC_ALIGN
namespace winograd_shim_nchw {
/***************************************************************************/
/* Implementation of the Winograd F(2x2, 3x3, 4x4) algorithm using GEMM
* internally.
*/
template <typename TOut, typename TIn>
class Winograd2x2_3x3GEMM : public winograd::Winograd2x2_3x3GEMM<TOut, TIn> {
public:
/* Instantiate a new Winograd operator.
*/
Winograd2x2_3x3GEMM(const KernelShape &kernel_shape, const Tensor4DShape input_shape, const PaddingType padding_type, void *kernel_storage);
void nchw2nhwc( const Tensor4DShape& input_shape, const PaddingType padding_type, void *working_space, const TIn* const input);
void nhwc2nchw( const Tensor4DShape& input_shape, const PaddingType padding_type, void *working_space, TOut* const output);
std::pair<TOut*,TIn*> get_nhwc_ptrs(const Tensor4DShape& input_shape,const PaddingType padding_type,void *working_space);
static size_t get_working_space_size(const Tensor4DShape &input_shape,const KernelShape &k_shape, const PaddingType padding);
protected:
/* Get the memory required to store an NHWC copy of the input tensor. */
static size_t get_working_nhwc_input_size(const Tensor4DShape &input_shape);
/* Get the memory required to store an NHWC copy of the input tensor. */
static size_t get_working_nhwc_output_size(const Tensor4DShape &output_shape, const KernelShape &k_shape, const PaddingType padding) ;
};
} // namespace winograd
/*****************************************************************************/
template <typename TOut, typename TIn>
winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::Winograd2x2_3x3GEMM(
const KernelShape &kernel_shape, const Tensor4DShape input_shape,
const PaddingType padding_type, void *kernel_storage
) : winograd::Winograd2x2_3x3GEMM<TOut, TIn>(kernel_shape,input_shape,padding_type,kernel_storage) {
}
/*****************************************************************************/
template <typename TOut, typename TIn>
void winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::nchw2nhwc(const Tensor4DShape& input_shape, const PaddingType padding_type, void *working_space, const TIn* const input) {
assert(working_space);
int8_t* const ws_bytes = reinterpret_cast<int8_t *>(working_space);
// Extract the top chunk of the working space to store the input and output
// tensors in NHWC format.
const int in_matrix_stride_bytes = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_input_matrix_size(input_shape, this->kernel_shape, padding_type);
const int out_matrix_stride_bytes = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_output_matrix_size(input_shape, this->kernel_shape, padding_type);
// Allocate working space for the input and output in NHWC format
TIn* const input_nhwc = reinterpret_cast<TIn *>(
ws_bytes + 16*(in_matrix_stride_bytes + out_matrix_stride_bytes)
);
// Re-order the input tensor
this->prof(
"NCHW -> NHWC",
[input, input_shape, input_nhwc] () {
nchw_to_nhwc(
input, input_nhwc,
input_shape.n_batches,
input_shape.n_channels,
input_shape.n_rows,
input_shape.n_cols
);
},
input_shape.size(), 0, input_shape.size()
);
}
/*****************************************************************************/
template <typename TOut, typename TIn>
void winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::nhwc2nchw(const Tensor4DShape& input_shape, const PaddingType padding_type,
void *working_space, TOut* const output) {
assert(working_space);
int8_t* const ws_bytes = reinterpret_cast<int8_t *>(working_space);
// Extract the top chunk of the working space to store the input and output
// tensors in NHWC format.
const int in_matrix_stride_bytes = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_input_matrix_size(input_shape, this->kernel_shape, padding_type);
const int out_matrix_stride_bytes = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_output_matrix_size(input_shape, this->kernel_shape, padding_type);
TOut* const output_nhwc = reinterpret_cast<TOut *>(ws_bytes + 16*(in_matrix_stride_bytes + out_matrix_stride_bytes) + get_working_nhwc_input_size(input_shape));
// Re-order the output tensor into NCHW
const auto output_shape = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_output_shape(input_shape, this->kernel_shape, padding_type);
this->prof(
"NHWC -> NCHW",
[output_nhwc, output_shape, output] () {
nhwc_to_nchw(
output_nhwc, output,
output_shape.n_batches,
output_shape.n_rows,
output_shape.n_cols,
output_shape.n_channels
);
},
output_shape.size(), 0, output_shape.size()
);
}
/*****************************************************************************/
template <typename TOut, typename TIn>
std::pair<TOut*,TIn*> winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::get_nhwc_ptrs(
const Tensor4DShape& input_shape,
const PaddingType padding_type,
void *working_space
) {
assert(working_space);
int8_t* const ws_bytes = reinterpret_cast<int8_t *>(working_space);
// Extract the top chunk of the working space to store the input and output
// tensors in NHWC format.
const int in_matrix_stride_bytes = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_input_matrix_size(input_shape, this->kernel_shape, padding_type);
const int out_matrix_stride_bytes = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_output_matrix_size(input_shape, this->kernel_shape, padding_type);
// Allocate working space for the input and output in NHWC format
TIn* input_nhwc = reinterpret_cast<TIn *>(ws_bytes + 16*(in_matrix_stride_bytes + out_matrix_stride_bytes));
TOut* output_nhwc = reinterpret_cast<TOut *>(ws_bytes + 16*(in_matrix_stride_bytes + out_matrix_stride_bytes) + get_working_nhwc_input_size(input_shape));
return std::make_pair(output_nhwc,input_nhwc);
}
/*****************************************************************************/
template <typename TOut, typename TIn>
size_t winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::get_working_space_size(
const Tensor4DShape& input_shape, const KernelShape &k_shape, const PaddingType padding_type
) {
// TODO Add memory required for NHWC copies of input tensors
return winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_working_space_size(
input_shape, k_shape, padding_type)
+ get_working_nhwc_input_size(input_shape)
+ get_working_nhwc_output_size(input_shape, k_shape, padding_type);
}
template <typename TOut, typename TIn>
size_t winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::get_working_nhwc_input_size(
const Tensor4DShape& input_shape
) {
return roundup(input_shape.size() * sizeof(TIn), static_cast<size_t>(ALLOC_ALIGN));
}
template <typename TOut, typename TIn>
size_t winograd_shim_nchw::Winograd2x2_3x3GEMM<TOut, TIn>::get_working_nhwc_output_size(
const Tensor4DShape& input_shape, const KernelShape &k_shape, const PaddingType padding_type
) {
const auto output_shape = winograd::Winograd2x2_3x3GEMM<TOut, TIn>::get_output_shape(input_shape,k_shape, padding_type);
return roundup(output_shape.size() * sizeof(TIn), static_cast<size_t>(ALLOC_ALIGN));
}
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