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/*
* Copyright (c) 2017-2018 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/NEON/kernels/NEDirectConvolutionLayerKernel.h"
#include "arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h"
#include "arm_compute/core/NEON/kernels/NEFillBorderKernel.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/IMemoryManager.h"
#include "arm_compute/runtime/MemoryGroup.h"
#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
#include "arm_compute/runtime/Tensor.h"
#include <memory>
namespace arm_compute
{
/** Function to run the direct convolution.
*
* This function calls the following NEON kernels:
*
* -# @ref NEFillBorderKernel for the input
* -# @ref NEDirectConvolutionLayerOutputStageKernel
* -# @ref NEDirectConvolutionLayerKernel
*/
class NEDirectConvolutionLayer : public IFunction
{
public:
/** Constructor */
NEDirectConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Set the input, weights, biases and output tensors.
*
* @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:
MemoryGroup _memory_group;
NEDirectConvolutionLayerOutputStageKernel _output_stage_kernel;
NEDirectConvolutionLayerKernel _conv_kernel;
NEFillBorderKernel _input_border_handler;
NEActivationLayer _activationlayer_function;
Tensor _accumulator;
bool _has_bias;
bool _is_activationlayer_enabled;
unsigned int _dim_split;
};
}
#endif /* __ARM_COMPUTE_NEDIRECTCONVOLUTIONLAYER_H__ */
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