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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_GCDIRECTCONVOLUTIONLAYERKERNEL_H__
#define __ARM_COMPUTE_GCDIRECTCONVOLUTIONLAYERKERNEL_H__
#include "arm_compute/core/GLES_COMPUTE/IGCKernel.h"
#include "arm_compute/core/GLES_COMPUTE/OpenGLES.h"
namespace arm_compute
{
class IGCTensor;
/** Interface for the direct convolution kernel.
*/
template <unsigned int kernel_size>
class GCDirectConvolutionLayerKernel : public IGCKernel
{
public:
/** Default constructor */
GCDirectConvolutionLayerKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
GCDirectConvolutionLayerKernel(const GCDirectConvolutionLayerKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
GCDirectConvolutionLayerKernel &operator=(const GCDirectConvolutionLayerKernel &) = delete;
/** Allow instances of this class to be moved */
GCDirectConvolutionLayerKernel(GCDirectConvolutionLayerKernel &&) = default;
/** Allow instances of this class to be moved */
GCDirectConvolutionLayerKernel &operator=(GCDirectConvolutionLayerKernel &&) = default;
/** Default destructor */
~GCDirectConvolutionLayerKernel() = 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: F16/F32
* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
* @param[in] bias Biases tensor. Shared bias supported. Biases are 1D tensor with dimensions [OFM]. Data type supported:Same as @p input.
* @param[out] output The output tensor. First 2 lower dimensions represent a transform of each 3D input,
* while every dimension above represents a batch. 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(const IGCTensor *input, const IGCTensor *weights, const IGCTensor *bias, IGCTensor *output,
const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info = ActivationLayerInfo());
// Inherited methods overridden:
BorderSize border_size() const override;
// Inherited methods overridden:
void run(const Window &window) override;
private:
const IGCTensor *_input;
const IGCTensor *_bias;
const IGCTensor *_weights;
IGCTensor *_output;
BorderSize _border_size;
int _conv_stride_x;
int _conv_stride_y;
int _conv_pad_x;
int _conv_pad_y;
gles::NDRange _lws;
};
/** Interface for the 1x1 direct convolution kernel */
using GCDirectConvolutionLayer1x1Kernel = GCDirectConvolutionLayerKernel<1>;
/** Interface for the 3x3 direct convolution kernel */
using GCDirectConvolutionLayer3x3Kernel = GCDirectConvolutionLayerKernel<3>;
/** Interface for the 5x5 direct convolution kernel */
using GCDirectConvolutionLayer5x5Kernel = GCDirectConvolutionLayerKernel<5>;
}
#endif /*__ARM_COMPUTE_GCDIRECTCONVOLUTIONLAYERKERNEL_H__ */
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