arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h

/*
 * 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
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 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 */
#ifndef __ARM_COMPUTE_CLDEPTHWISECONVOLUTION_H__
#define __ARM_COMPUTE_CLDEPTHWISECONVOLUTION_H__

#include "arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h"
#include "arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h"
#include "arm_compute/core/CL/kernels/CLDepthwiseIm2ColKernel.h"
#include "arm_compute/core/CL/kernels/CLDepthwiseVectorToTensorKernel.h"
#include "arm_compute/core/CL/kernels/CLDepthwiseWeightsReshapeKernel.h"
#include "arm_compute/core/CL/kernels/CLDirectConvolutionLayerOutputStageKernel.h"
#include "arm_compute/core/CL/kernels/CLFillBorderKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.h"
#include "arm_compute/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/CL/CLMemoryGroup.h"
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
#include "arm_compute/runtime/CL/functions/CLPermute.h"
#include "arm_compute/runtime/IFunction.h"

namespace arm_compute
{
class ICLTensor;

/** Basic function to execute a depthwise convolution for kernel size 3x3xC (when data layout NCHW) or Cx3x3 (when data layout NHWC). This function calls the following OpenCL kernels:
 *
 * -# @ref CLDepthwiseConvolutionLayer3x3NCHWKernel (if data_layout == NCHW)
 * -# @ref CLDepthwiseConvolutionLayer3x3NHWCKernel (if data_layout == NHWC)
 * -# @ref CLFillBorderKernel (if pad_x or pad_y > 0)
 *
 */
class CLDepthwiseConvolutionLayer3x3 : public IFunction
{
public:
    /** Default constructor */
    CLDepthwiseConvolutionLayer3x3(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
    /** Prevent instances of this class from being copied (As this class contains pointers) */
    CLDepthwiseConvolutionLayer3x3(const CLDepthwiseConvolutionLayer3x3 &) = delete;
    /** Default move constructor */
    CLDepthwiseConvolutionLayer3x3(CLDepthwiseConvolutionLayer3x3 &&) = default;
    /** Prevent instances of this class from being copied (As this class contains pointers) */
    CLDepthwiseConvolutionLayer3x3 &operator=(const CLDepthwiseConvolutionLayer3x3 &) = delete;
    /** Default move assignment operator */
    CLDepthwiseConvolutionLayer3x3 &operator=(CLDepthwiseConvolutionLayer3x3 &&) = default;
    /** Initialize the function's source, destination, conv and border_size.
     *
     * @param[in, out] input            Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
     * @param[in]      weights          Weights tensor. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input.
     * @param[in]      biases           (Optional) Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
     *                                  Data type supported: Same as @p input.
     * @param[out]     output           Destination tensor. Data type supported: same as @p input.
     * @param[in]      conv_info        Padding and stride information to use for the convolution.
     * @param[in]      depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
     * @param[in]      act_info         (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported.
     */
    void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
                   ActivationLayerInfo act_info = ActivationLayerInfo());

    /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3
     *
     * @param[in] input            Source tensor. Data type supported: QASYMM8 for all layouts, F16/F32 for NCHW.
     * @param[in] weights          Weights tensor. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input.
     * @param[in] biases           Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
     *                             Data type supported: Same as @p input, S32 when input is QASYMM8.
     * @param[in] output           Destination tensor. Data type supported: same as @p input.
     * @param[in] conv_info        Padding and stride information to use for the convolution.
     * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
     * @param[in] act_info         (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported.
     * @param[in] gpu_target       (Optional) GPU target to validate the kernel for. Defaults to midgard.
     *
     * @return a status
     */
    static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
                           ActivationLayerInfo act_info = ActivationLayerInfo(), GPUTarget gpu_target = GPUTarget::MIDGARD);
    // Inherited methods overriden:
    void run() override;
    void prepare() override;

private:
    CLMemoryGroup                                          _memory_group;
    std::unique_ptr<ICLDepthwiseConvolutionLayer3x3Kernel> _kernel;
    CLFillBorderKernel                                     _border_handler;
    CLPermute                                              _permute_input_to_nchw;
    CLPermute                                              _permute_weights_to_nchw;
    CLPermute                                              _permute_output_to_nhwc;
    CLTensor                                               _permuted_input;
    CLTensor                                               _permuted_weights;
    CLTensor                                               _permuted_output;
    const ITensor                                         *_original_weights;
    bool                                                   _needs_permute;
    bool                                                   _is_prepared;
};

/** Basic function to execute a generic depthwise convolution. This function calls the following OpenCL kernels:
 *
 * -# @ref CLDepthwiseIm2ColKernel
 * -# @ref CLGEMMMatrixVectorMultiplyKernel
 * -# @ref CLDepthwiseWeightsReshapeKernel
 * -# @ref CLFillBorderKernel (if pad_x or pad_y > 0)
 *
 */
class CLDepthwiseConvolutionLayer : public IFunction
{
public:
    /** Default constructor */
    CLDepthwiseConvolutionLayer();
    /** Prevent instances of this class from being copied (As this class contains pointers) */
    CLDepthwiseConvolutionLayer(const CLDepthwiseConvolutionLayer &) = delete;
    /** Default move constructor */
    CLDepthwiseConvolutionLayer(CLDepthwiseConvolutionLayer &&) = default;
    /** Prevent instances of this class from being copied (As this class contains pointers) */
    CLDepthwiseConvolutionLayer &operator=(const CLDepthwiseConvolutionLayer &) = delete;
    /** Default move assignment operator */
    CLDepthwiseConvolutionLayer &operator=(CLDepthwiseConvolutionLayer &&) = default;
    /** Initialize the function's source, destination, weights and convolution information.
     *
     * @param[in, out] input            Source tensor. Data type supported: QASYMM8/F32. (Written to only for border filling).
     * @param[in]      weights          Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input.
     * @param[in]      biases           (Optional) Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
     *                                  Data type supported: Same as @p input, S32 when input is QASYMM8.
     * @param[out]     output           Destination tensor. Data type supported: same as @p input.
     * @param[in]      conv_info        Padding and stride information to use for the convolution.
     * @param[in]      depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
     * @param[in]      act_info         (Optional) Activation layer information in case of a fused activation.
     */
    void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
                   unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo());

    /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer
     *
     * @param[in] input            Source tensor. Data type supported: QASYMM8/F32.
     * @param[in] weights          Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input.
     * @param[in] biases           Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
     *                             Data type supported: Same as @p input, S32 when input is QASYMM8.
     * @param[in] output           Destination tensor. Data type supported: same as @p input.
     * @param[in] conv_info        Padding and stride information to use for the convolution.
     * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
     * @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 *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
                           unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo());

    // Inherited methods overriden:
    void run() override;
    void prepare() override;

private:
    CLDepthwiseIm2ColKernel                   _im2col_kernel;
    CLDepthwiseWeightsReshapeKernel           _weights_reshape_kernel;
    CLGEMMMatrixVectorMultiplyKernel          _v2mm_kernel;
    CLDepthwiseVectorToTensorKernel           _vector_to_tensor_kernel;
    CLDirectConvolutionLayerOutputStageKernel _output_stage_kernel;
    CLActivationLayer                         _activationlayer_function;
    CLFillBorderKernel                        _v2mm_input_fill_border;
    CLFillBorderKernel                        _v2mm_weights_fill_border;
    CLTensor                                  _input_reshaped;
    CLTensor                                  _weights_reshaped;
    CLTensor                                  _v2mm_output;
    CLTensor                                  _output_reshaped;
    bool                                      _is_prepared;
    bool                                      _is_quantized;
    bool                                      _is_activationlayer_enabled;
    const ICLTensor                          *_original_weights;
    std::unique_ptr<IFunction>                _optimised_function;
};
} // namespace arm_compute
#endif /*__ARM_COMPUTE_CLDEPTHWISECONVOLUTION_H__ */