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/*
* Copyright (c) 2017-2020 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 __ARM_COMPUTE_NEIM2COLKERNEL_H__
#define __ARM_COMPUTE_NEIM2COLKERNEL_H__
#include "arm_compute/core/NEON/INEKernel.h"
namespace arm_compute
{
class ITensor;
class Size2D;
/** Interface for the im2col reshape kernel.
*
* Rearranges image blocks into columns. It is used to strip out each convolution block to a single column.
* It is used to transform a convolution to a plain matrix multiplication.
*
* For example taking into account the image below and assuming 3x3 image blocks with stride of 1 we have:
*
* @f[
* \left( \begin{array}{cccc}
* a00 & a01 & a02 & a03 \\
* a10 & a11 & a12 & a13 \\
* a20 & a21 & a22 & a23 \\
* a30 & a31 & a32 & a33 \\
* \end{array} \right)
* \rightarrow
* \left( \begin{array}{ccccccccc}
* a00 & a01 & a02 & a10 & a11 & a12 & a20 & a21 & a22 \\
* a01 & a02 & a03 & a11 & a12 & a13 & a21 & a22 & a23 \\
* a10 & a11 & a12 & a20 & a21 & a22 & a30 & a31 & a32 \\
* a11 & a12 & a13 & a21 & a22 & a23 & a31 & a32 & a33 \\
* \end{array} \right)
* @f]
*/
class NEIm2ColKernel : public INEKernel
{
public:
const char *name() const override
{
return "NEIm2ColKernel";
}
/** Default constructor */
NEIm2ColKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEIm2ColKernel(const NEIm2ColKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEIm2ColKernel &operator=(const NEIm2ColKernel &) = delete;
/** Allow instances of this class to be moved */
NEIm2ColKernel(NEIm2ColKernel &&) = default;
/** Allow instances of this class to be moved */
NEIm2ColKernel &operator=(NEIm2ColKernel &&) = default;
/** Default destructor */
~NEIm2ColKernel() = default;
/** Set the input and output of the kernel.
*
* @param[in] input The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
* while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8/F16/F32
* Note: QASYMM8 works only for has_bias = false
* @param[out] output The output tensor. Data types supported: Same as @p input
* @param[in] kernel_dims The kernel dimensions (width and height).
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @param[in] has_bias In case biases are provided expands the matrix with 1.
* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
* @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is not supported
*/
void configure(const ITensor *input, ITensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info,
bool has_bias, const Size2D &dilation = Size2D(1U, 1U), unsigned int num_groups = 1);
/** Static function to check if given info will lead to a valid configuration of @ref NEIm2ColKernel
*
* @param[in] input The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
* while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8/F16/F32
* Note: QASYMM8 works only for has_bias = false
* @param[in] output The output tensor. Data types supported: Same as @p input
* @param[in] kernel_dims The kernel dimensions (width and height).
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @param[in] has_bias In case biases are provided expands the matrix with 1.
* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
* @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is not supported
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info,
bool has_bias, const Size2D &dilation = Size2D(1U, 1U), unsigned int num_groups = 1);
// Inherited methods overridden:
void run(const Window &window, const ThreadInfo &info) override;
private:
/** Template function to run im2col
*
* @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).
*/
template <typename T, bool has_pads, bool is_nchw>
void run_im2col(const Window &window);
/** Common signature for all the specialised im2col functions
*
* @param[in] window Region on which to execute the kernel.
*/
using Im2ColFunctionPtr = void (NEIm2ColKernel::*)(const Window &window);
Im2ColFunctionPtr _func;
const ITensor *_input;
ITensor *_output;
std::pair<unsigned int, unsigned int> _convolved_dims;
PadStrideInfo _conv_info;
unsigned int _kernel_width;
unsigned int _kernel_height;
bool _has_bias;
Size2D _dilation;
DataLayout _data_layout;
};
} // namespace arm_compute
#endif /*__ARM_COMPUTE_NEIM2COLKERNEL_H__ */
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