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/*
* Copyright (c) 2017-2021, 2023 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_NEDIRECTCONVOLUTIONLAYER_H
#define ARM_COMPUTE_NEDIRECTCONVOLUTIONLAYER_H
#include "arm_compute/core/Types.h"
#include "arm_compute/function_info/ActivationLayerInfo.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/IMemoryManager.h"
#include "arm_compute/runtime/MemoryGroup.h"
#include <memory>
namespace arm_compute
{
class ITensor;
class ITensorInfo;
/** Function to run the direct convolution.
*
* This function calls the following:
*
* -# @ref cpu::CpuDirectConv2d
*/
class NEDirectConvolutionLayer : public IFunction
{
public:
/** Constructor */
NEDirectConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEDirectConvolutionLayer(const NEDirectConvolutionLayer &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEDirectConvolutionLayer &operator=(const NEDirectConvolutionLayer &) = delete;
/** Prevent instances of this class from being moved (As this class contains non movable objects) */
NEDirectConvolutionLayer(NEDirectConvolutionLayer &&) = delete;
/** Prevent instances of this class from being moved (As this class contains non movable objects) */
NEDirectConvolutionLayer &operator=(NEDirectConvolutionLayer &&) = delete;
/** Default destructor */
~NEDirectConvolutionLayer();
/** Set the input, weights, biases and output tensors.
*
* Valid data layouts:
* - NHWC
* - NCHW
*
* Valid data type configurations:
* |src0 |src1 |src2 |dst |
* |:------|:------|:------|:------|
* |F16 |F16 |F16 |F16 |
* |F32 |F32 |F32 |F32 |
*
* @note: DirectConvolution only works in the following configurations:
* 1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
* 3x3 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
* 5x5 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F32
*
* @param[in, out] input Input tensor. Data types supported: F16/F32.
* @param[in] weights Set of kernels to convolve the input volume.
* Supported sizes: 1x1, 3x3 and 5x5.
* The 3rd dimension must be the same as the input's volume 3rd dimension.
* Data type supported: Same as @p input.
* @param[in] bias Set of biases. Can be nullptr. Data type supported: Same as @p input.
* @param[out] output Output tensor.
* The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: Same as @p input.
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
*/
void configure(ITensor *input,
const ITensor *weights,
const ITensor *bias,
ITensor *output,
const PadStrideInfo &conv_info,
const ActivationLayerInfo &act_info = ActivationLayerInfo());
/** Static function to check if given info will lead to a valid configuration of @ref NEDirectConvolutionLayer
*
* @note: DirectConvolution only works in the following configurations:
* 1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
* 3x3 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
* 5x5 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F32
*
* @param[in] input Input tensor. Data types supported: F16/F32.
* @param[in] weights Set of kernels to convolve the input volume.
* Supported sizes: 1x1, 3x3 and 5x5.
* The 3rd dimension must be the same as the input's volume 3rd dimension.
* Data type supported: Same as @p input.
* @param[in] bias Set of biases. Can be nullptr. Data type supported: Same as @p input.
* @param[in] output Output tensor.
* The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: Same as @p input.
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
*
* @return a status
*/
static Status validate(const ITensorInfo *input,
const ITensorInfo *weights,
const ITensorInfo *bias,
const ITensorInfo *output,
const PadStrideInfo &conv_info,
const ActivationLayerInfo &act_info = ActivationLayerInfo());
// Inherited methods overridden:
void run() override;
private:
struct Impl;
std::shared_ptr<IMemoryManager> _memory_manager;
std::unique_ptr<Impl> _impl;
};
} // namespace arm_compute
#endif /* ARM_COMPUTE_NEDIRECTCONVOLUTIONLAYER_H */
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