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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_GCCONVOLUTIONLAYER_H__
#define __ARM_COMPUTE_GCCONVOLUTIONLAYER_H__
#include "arm_compute/core/GLES_COMPUTE/kernels/GCCol2ImKernel.h"
#include "arm_compute/core/GLES_COMPUTE/kernels/GCFillBorderKernel.h"
#include "arm_compute/core/GLES_COMPUTE/kernels/GCIm2ColKernel.h"
#include "arm_compute/core/GLES_COMPUTE/kernels/GCWeightsReshapeKernel.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/GLES_COMPUTE/GCMemoryGroup.h"
#include "arm_compute/runtime/GLES_COMPUTE/GCTensor.h"
#include "arm_compute/runtime/GLES_COMPUTE/functions/GCActivationLayer.h"
#include "arm_compute/runtime/GLES_COMPUTE/functions/GCGEMM.h"
#include "arm_compute/runtime/IFunction.h"
#include <memory>
namespace arm_compute
{
class IGCTensor;
/** Function to reshape and transpose the weights. This function calls the following kernels:
* -# @ref GCWeightsReshapeKernel
*/
class GCConvolutionLayerReshapeWeights : public IFunction
{
public:
/** Constructor */
GCConvolutionLayerReshapeWeights();
/** Set the input and output tensors.
*
* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
* Data type supported: F16/F32.
* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights.
* @param[out] output Destination tensor. Data types supported: Same as @p weights.
*/
void configure(const IGCTensor *weights, const IGCTensor *biases, IGCTensor *output);
// Inherited methods overridden:
void run() override;
private:
GCWeightsReshapeKernel _weights_reshape_kernel;
};
/** Basic function to compute the convolution layer. This function calls the following GLES kernels:
*
* -# @ref GCWeightsReshapeKernel (executed only once for each configuration)
* -# @ref GCGEMMTranspose1xWKernel (executed only once for each configuration)
* -# @ref GCIm2ColKernel
* -# @ref GCGEMMInterleave4x4Kernel
* -# @ref GCCol2ImKernel
*/
class GCConvolutionLayer : public IFunction
{
public:
/** Default constructor */
GCConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Prevent instances of this class from being copied (As this class contains pointers) */
GCConvolutionLayer(const GCConvolutionLayer &) = delete;
/** Default move constructor */
GCConvolutionLayer(GCConvolutionLayer &&) = default;
/** Prevent instances of this class from being copied (As this class contains pointers) */
GCConvolutionLayer &operator=(const GCConvolutionLayer &) = delete;
/** Default move assignment operator */
GCConvolutionLayer &operator=(GCConvolutionLayer &&) = default;
/** Set the input and output tensors.
*
* @param[in] input Source tensor. 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] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
* Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type.
* @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
* Data types supported: Same as @p input.
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @param[in] weights_info Specifies if the weights tensor has been reshaped with GCWeightsReshapeKernel. If this is not part of the fully connected layer the weights
* tensor has also been transposed with GCGEMMTranspose1xWKernel. Data type supported: Same as @p input.
* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
* @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is not supported
*/
void configure(const IGCTensor *input, const IGCTensor *weights, const IGCTensor *biases, IGCTensor *output, const PadStrideInfo &conv_info,
const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1);
// Inherited methods overridden:
void run() override;
void prepare() override;
private:
/** Configures the appropriate matrix multiply routine
*
* @param input Input tensor. Data types supported: F16/F32.
* @param weights Weights tensor. Data type supported: Same as @p input.
* @param output Output tensor. Data types supported: Same as @p input,
*/
void configure_mm(const IGCTensor *input, const IGCTensor *weights, IGCTensor *output);
/** Static function to check if given info will lead to a valid configuration of @ref GCGEMMConvolutionLayer matrix multiply routines
*
* @param[in] input Input tensor. Data types supported: QASYMM8/F16/F32.
* @param[in] weights Weights tensor. Data type supported: Same as @p input.
* @param[in] output Output tensor. Data types supported: Same as @p input,
* except for input of QASYMM8 type where output should be of S32 type.
*
* @return a status
*/
static Status validate_mm(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *output);
private:
GCMemoryGroup _memory_group;
GCConvolutionLayerReshapeWeights _reshape_weights;
GCIm2ColKernel _input_im2col_kernel;
GCGEMM _mm_gemm;
GCCol2ImKernel _output_col2im_kernel;
GCFillBorderKernel _fill_border;
GCActivationLayer _activationlayer_function;
const IGCTensor *_original_weights;
GCTensor _input_im2col_reshaped;
GCTensor _input_interleaved_reshaped;
GCTensor _weights_reshaped;
GCTensor _weights_transposed;
GCTensor _gemm_output;
GCTensor _tmp_output;
bool _is_activationlayer_enabled;
bool _is_prepared;
};
}
#endif /* __ARM_COMPUTE_GCCONVOLUTIONLAYER_H__ */
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