arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h - ml/ComputeLibrary - Gitiles

 /*
  * Copyright (c) 2017-2019 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_NEDEPTHWISECONVOLUTION_H__
 #define __ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H__

 #include "arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayer3x3Kernel.h"
 #include "arm_compute/core/NEON/kernels/NEDepthwiseIm2ColKernel.h"
 #include "arm_compute/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.h"
 #include "arm_compute/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.h"
 #include "arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h"
 #include "arm_compute/core/NEON/kernels/NEFillBorderKernel.h"
 #include "arm_compute/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.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/NEON/functions/NEPermute.h"
 #include "arm_compute/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.h"
 #include "arm_compute/runtime/Tensor.h"

 namespace arm_compute
 {
 class ITensor;

 /** Basic function to execute a depthwise convolution for kernel size 3x3xC. This function calls the following NEON kernels:
  *
  * -# @ref NEDepthwiseConvolutionLayer3x3
  * -# @ref NEFillBorderKernel (if pad_x or pad_y > 0)
  *
  */
 class NEDepthwiseConvolutionLayer3x3 : public IFunction
 {
 public:
     /** Default constructor */
     NEDepthwiseConvolutionLayer3x3(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
     /** Prevent instances of this class from being copied (As this class contains pointers) */
     NEDepthwiseConvolutionLayer3x3(const NEDepthwiseConvolutionLayer3x3 &) = delete;
     /** Default move constructor */
     NEDepthwiseConvolutionLayer3x3(NEDepthwiseConvolutionLayer3x3 &&) = default;
     /** Prevent instances of this class from being copied (As this class contains pointers) */
     NEDepthwiseConvolutionLayer3x3 &operator=(const NEDepthwiseConvolutionLayer3x3 &) = delete;
     /** Default move assignment operator */
     NEDepthwiseConvolutionLayer3x3 &operator=(NEDepthwiseConvolutionLayer3x3 &&) = default;
     /** Initialize the function's source, destination, kernels 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. These are 3D tensors 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.
      */
     void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *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 NEDepthwiseConvolutionLayer3x3
      *
      * @param[in] input            Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
      * @param[in] weights          Weights tensor. These are 3D tensors 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[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:
     /** Configure the kernels/functions for the generic pipeline.
      *
      * @param[in, out] input            Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
      * @param[in]      weights          Weights tensor. These are 3D tensors 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 Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in]      act_info         Activation layer information in case of a fused activation.
      */
     void configure_generic(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info,
                            unsigned int depth_multiplier, const ActivationLayerInfo &act_info);
     /** Configure the kernels/functions for the optimized pipeline.
      *
      * @param[in]  input            Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
      * @param[in]  weights          Weights tensor. These are 3D tensors 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 Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in]  act_info         Activation layer information in case of a fused activation.
      */
     void configure_optimized(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info,
                              unsigned int depth_multiplier, const ActivationLayerInfo &act_info);
     /** Run generic kernel */
     void run_generic();
     /** Run optimized function */
     void run_optimized();

 private:
     MemoryGroup                               _memory_group;
     NEDepthwiseConvolutionLayer3x3Kernel      _dwc_kernel;
     NEDepthwiseConvolutionAssemblyDispatch    _dwc_optimized_func;
     NEDirectConvolutionLayerOutputStageKernel _output_stage_kernel;
     NEFillBorderKernel                        _border_handler;
     NEPermute                                 _permute_input;
     NEPermute                                 _permute_weights;
     NEPermute                                 _permute_output;
     NEActivationLayer                         _activationlayer_function;
     Tensor                                    _accumulator;
     Tensor                                    _permuted_input;
     Tensor                                    _permuted_weights;
     Tensor                                    _permuted_output;
     const ITensor                            *_original_weights;
     bool                                      _has_bias;
     bool                                      _is_quantized;
     bool                                      _is_optimized;
     bool                                      _is_nchw;
     bool                                      _permute;
     bool                                      _is_activationlayer_enabled;
     bool                                      _is_prepared;
 };

 /** Basic function to execute a generic depthwise convolution. This function calls the following NEON kernels:
  *
  * -# @ref NEDepthwiseIm2ColKernel
  * -# @ref NEDepthwiseWeightsReshapeKernel
  * -# @ref NEGEMMMatrixVectorMultiplyKernel
  * -# @ref NEFillBorderKernel (if pad_x or pad_y > 0)
  *
  */
 class NEDepthwiseConvolutionLayer : public IFunction
 {
 public:
     /** Default constructor */
     NEDepthwiseConvolutionLayer();
     /** Prevent instances of this class from being copied (As this class contains pointers) */
     NEDepthwiseConvolutionLayer(const NEDepthwiseConvolutionLayer &) = delete;
     /** Default move constructor */
     NEDepthwiseConvolutionLayer(NEDepthwiseConvolutionLayer &&) = default;
     /** Prevent instances of this class from being copied (As this class contains pointers) */
     NEDepthwiseConvolutionLayer &operator=(const NEDepthwiseConvolutionLayer &) = delete;
     /** Default move assignment operator */
     NEDepthwiseConvolutionLayer &operator=(NEDepthwiseConvolutionLayer &&) = default;
     /** Initialize the function's source, destination, weights and convolution information.
      *
      * @param[in, out] input            Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
      * @param[out]     output           Destination tensor. Data type supported: same as @p input.
      * @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[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(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *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 NEDepthwiseConvolutionLayer
      *
      * @param[in] input            Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
      * @param[in] output           Destination tensor. Data type supported: same as @p input.
      * @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[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:
     NEDepthwiseIm2ColKernel                   _im2col_kernel;
     NEDepthwiseWeightsReshapeKernel           _weights_reshape_kernel;
     NEGEMMMatrixVectorMultiplyKernel          _v2mm_kernel;
     NEDepthwiseVectorToTensorKernel           _vector_to_tensor_kernel;
     NEDirectConvolutionLayerOutputStageKernel _output_stage_kernel;
     NEFillBorderKernel                        _v2mm_input_fill_border;
     NEFillBorderKernel                        _v2mm_weights_fill_border;
     NEPermute                                 _permute_input;
     NEPermute                                 _permute_weights;
     NEPermute                                 _permute_output;
     NEActivationLayer                         _activationlayer_function;
     Tensor                                    _input_reshaped;
     Tensor                                    _weights_reshaped;
     Tensor                                    _v2mm_output;
     Tensor                                    _output_reshaped;
     Tensor                                    _permuted_input;
     Tensor                                    _permuted_weights;
     Tensor                                    _permuted_output;
     bool                                      _is_prepared;
     bool                                      _is_quantized;
     bool                                      _is_nhwc;
     bool                                      _is_activationlayer_enabled;
     const ITensor                            *_original_weights;
 };
 } // namespace arm_compute
 #endif /* __ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H__ */
	/*
	* Copyright (c) 2017-2019 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_NEDEPTHWISECONVOLUTION_H__
	#define __ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H__

	#include "arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayer3x3Kernel.h"
	#include "arm_compute/core/NEON/kernels/NEDepthwiseIm2ColKernel.h"
	#include "arm_compute/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.h"
	#include "arm_compute/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.h"
	#include "arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h"
	#include "arm_compute/core/NEON/kernels/NEFillBorderKernel.h"
	#include "arm_compute/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.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/NEON/functions/NEPermute.h"
	#include "arm_compute/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.h"
	#include "arm_compute/runtime/Tensor.h"

	namespace arm_compute
	{
	class ITensor;

	/** Basic function to execute a depthwise convolution for kernel size 3x3xC. This function calls the following NEON kernels:
	*
	* -# @ref NEDepthwiseConvolutionLayer3x3
	* -# @ref NEFillBorderKernel (if pad_x or pad_y > 0)
	*
	*/
	class NEDepthwiseConvolutionLayer3x3 : public IFunction
	{
	public:
	/** Default constructor */
	NEDepthwiseConvolutionLayer3x3(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
	/** Prevent instances of this class from being copied (As this class contains pointers) */
	NEDepthwiseConvolutionLayer3x3(const NEDepthwiseConvolutionLayer3x3 &) = delete;
	/** Default move constructor */
	NEDepthwiseConvolutionLayer3x3(NEDepthwiseConvolutionLayer3x3 &&) = default;
	/** Prevent instances of this class from being copied (As this class contains pointers) */
	NEDepthwiseConvolutionLayer3x3 &operator=(const NEDepthwiseConvolutionLayer3x3 &) = delete;
	/** Default move assignment operator */
	NEDepthwiseConvolutionLayer3x3 &operator=(NEDepthwiseConvolutionLayer3x3 &&) = default;
	/** Initialize the function's source, destination, kernels 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. These are 3D tensors 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.
	*/
	void configure(ITensor input, const ITensor weights, const ITensor biases, ITensor 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 NEDepthwiseConvolutionLayer3x3
	*
	* @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
	* @param[in] weights Weights tensor. These are 3D tensors 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[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:
	/** Configure the kernels/functions for the generic pipeline.
	*
	* @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
	* @param[in] weights Weights tensor. These are 3D tensors 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 Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
	* @param[in] act_info Activation layer information in case of a fused activation.
	*/
	void configure_generic(ITensor input, const ITensor weights, const ITensor biases, ITensor output, const PadStrideInfo &conv_info,
	unsigned int depth_multiplier, const ActivationLayerInfo &act_info);
	/** Configure the kernels/functions for the optimized pipeline.
	*
	* @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
	* @param[in] weights Weights tensor. These are 3D tensors 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 Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
	* @param[in] act_info Activation layer information in case of a fused activation.
	*/
	void configure_optimized(const ITensor input, const ITensor weights, const ITensor biases, ITensor output, const PadStrideInfo &conv_info,
	unsigned int depth_multiplier, const ActivationLayerInfo &act_info);
	/** Run generic kernel */
	void run_generic();
	/** Run optimized function */
	void run_optimized();

	private:
	MemoryGroup _memory_group;
	NEDepthwiseConvolutionLayer3x3Kernel _dwc_kernel;
	NEDepthwiseConvolutionAssemblyDispatch _dwc_optimized_func;
	NEDirectConvolutionLayerOutputStageKernel _output_stage_kernel;
	NEFillBorderKernel _border_handler;
	NEPermute _permute_input;
	NEPermute _permute_weights;
	NEPermute _permute_output;
	NEActivationLayer _activationlayer_function;
	Tensor _accumulator;
	Tensor _permuted_input;
	Tensor _permuted_weights;
	Tensor _permuted_output;
	const ITensor *_original_weights;
	bool _has_bias;
	bool _is_quantized;
	bool _is_optimized;
	bool _is_nchw;
	bool _permute;
	bool _is_activationlayer_enabled;
	bool _is_prepared;
	};

	/** Basic function to execute a generic depthwise convolution. This function calls the following NEON kernels:
	*
	* -# @ref NEDepthwiseIm2ColKernel
	* -# @ref NEDepthwiseWeightsReshapeKernel
	* -# @ref NEGEMMMatrixVectorMultiplyKernel
	* -# @ref NEFillBorderKernel (if pad_x or pad_y > 0)
	*
	*/
	class NEDepthwiseConvolutionLayer : public IFunction
	{
	public:
	/** Default constructor */
	NEDepthwiseConvolutionLayer();
	/** Prevent instances of this class from being copied (As this class contains pointers) */
	NEDepthwiseConvolutionLayer(const NEDepthwiseConvolutionLayer &) = delete;
	/** Default move constructor */
	NEDepthwiseConvolutionLayer(NEDepthwiseConvolutionLayer &&) = default;
	/** Prevent instances of this class from being copied (As this class contains pointers) */
	NEDepthwiseConvolutionLayer &operator=(const NEDepthwiseConvolutionLayer &) = delete;
	/** Default move assignment operator */
	NEDepthwiseConvolutionLayer &operator=(NEDepthwiseConvolutionLayer &&) = default;
	/** Initialize the function's source, destination, weights and convolution information.
	*
	* @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
	* @param[out] output Destination tensor. Data type supported: same as @p input.
	* @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[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(ITensor input, const ITensor weights, const ITensor biases, ITensor 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 NEDepthwiseConvolutionLayer
	*
	* @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
	* @param[in] output Destination tensor. Data type supported: same as @p input.
	* @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[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:
	NEDepthwiseIm2ColKernel _im2col_kernel;
	NEDepthwiseWeightsReshapeKernel _weights_reshape_kernel;
	NEGEMMMatrixVectorMultiplyKernel _v2mm_kernel;
	NEDepthwiseVectorToTensorKernel _vector_to_tensor_kernel;
	NEDirectConvolutionLayerOutputStageKernel _output_stage_kernel;
	NEFillBorderKernel _v2mm_input_fill_border;
	NEFillBorderKernel _v2mm_weights_fill_border;
	NEPermute _permute_input;
	NEPermute _permute_weights;
	NEPermute _permute_output;
	NEActivationLayer _activationlayer_function;
	Tensor _input_reshaped;
	Tensor _weights_reshaped;
	Tensor _v2mm_output;
	Tensor _output_reshaped;
	Tensor _permuted_input;
	Tensor _permuted_weights;
	Tensor _permuted_output;
	bool _is_prepared;
	bool _is_quantized;
	bool _is_nhwc;
	bool _is_activationlayer_enabled;
	const ITensor *_original_weights;
	};
	} // namespace arm_compute
	#endif /* __ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H__ */