blob: 8160310da611239d880595d63d3d684f433120d1 [file] [log] [blame]
/*
* Copyright (c) 2017-2022 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_CPU_IM2COL_KERNEL_H
#define ARM_COMPUTE_CPU_IM2COL_KERNEL_H
#include "arm_compute/core/Size2D.h"
#include "src/core/common/Macros.h"
#include "src/cpu/ICpuKernel.h"
namespace arm_compute
{
class ITensor;
namespace cpu
{
namespace kernels
{
/** 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 CpuIm2ColKernel : public ICpuKernel<CpuIm2ColKernel>
{
public:
/** Default constructor */
CpuIm2ColKernel() = default;
ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuIm2ColKernel);
/** Set the input and output of the kernel.
*
* @param[in] src The input tensor info 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/QASYMM8_SIGNED/BFLOAT16/F16/F32
* Note: QASYMM8/QASYMM8_SIGNED works only for has_bias = false
* @param[out] dst The output tensor info. 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 ITensorInfo *src, ITensorInfo *dst, 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
*
* Similar to CpuIm2ColKernel::configure()
*
* @return a status
*/
static Status validate(const ITensorInfo *src, const ITensorInfo *dst, 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_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override;
const char *name() const override;
/** Return minimum workload size of the relevant kernel
*
* @param[in] platform The CPU platform used to create the context.
* @param[in] thread_count Number of threads in the execution.
*
* @return[out] small_network_mws Minimum workload size for requsted configuration.
*/
size_t get_mws(const CPUInfo &platform, size_t thread_count) const override;
private:
/** Template function to run im2col
*
* @param[in] src The input tensor info
* @param[out] dst The output tensor info
* @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 ITensor *src, ITensor *dst, const Window &window);
/** Common signature for all the specialised im2col functions
*
* @param[in] window Region on which to execute the kernel.
*/
using Im2ColFunctionPtr = void (CpuIm2ColKernel::*)(const ITensor *src, ITensor *dst, const Window &window);
Im2ColFunctionPtr _func{ nullptr };
std::pair<unsigned int, unsigned int> _convolved_dims{};
PadStrideInfo _conv_info{};
unsigned int _kernel_width{ 0 };
unsigned int _kernel_height{ 0 };
bool _has_bias{ false };
Size2D _dilation{ 1U, 1U };
DataLayout _data_layout{ DataLayout::UNKNOWN };
};
} // namespace kernels
} // namespace cpu
} // namespace arm_compute
#endif /*ARM_COMPUTE_CPU_IM2COL_KERNEL_H */