COMPMID-2515: Merge optimized depthwise convolution to the generic depthwise convolution function

3RDPARTY_UPDATE

Change-Id: Iff9e915c5329c617527b6f5042979f4e21a8b2b8
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2022
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

1 files changed, 220 insertions, 195 deletions

diff --git a/arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h
index ea3ef9bf38..8fe9644963 100644
--- a/arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h
@@ -37,48 +37,43 @@ namespace arm_compute
 // Forward declarations
 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)
- *
+/** Function to execute a depthwise convolution.
  */
-class NEDepthwiseConvolutionLayer3x3 : public IFunction
+class NEDepthwiseConvolutionLayer : public IFunction
 {
 public:
     /** Default constructor */
-    NEDepthwiseConvolutionLayer3x3(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+    NEDepthwiseConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
     /** Prevent instances of this class from being copied (As this class contains pointers) */
-    NEDepthwiseConvolutionLayer3x3(const NEDepthwiseConvolutionLayer3x3 &) = delete;
+    NEDepthwiseConvolutionLayer(const NEDepthwiseConvolutionLayer &) = delete;
     /** Default move constructor */
-    NEDepthwiseConvolutionLayer3x3(NEDepthwiseConvolutionLayer3x3 &&) = default;
+    NEDepthwiseConvolutionLayer(NEDepthwiseConvolutionLayer &&) = default;
     /** Prevent instances of this class from being copied (As this class contains pointers) */
-    NEDepthwiseConvolutionLayer3x3 &operator=(const NEDepthwiseConvolutionLayer3x3 &) = delete;
+    NEDepthwiseConvolutionLayer &operator=(const NEDepthwiseConvolutionLayer &) = delete;
     /** Default move assignment operator */
-    NEDepthwiseConvolutionLayer3x3 &operator=(NEDepthwiseConvolutionLayer3x3 &&) = default;
-    /** Initialize the function's source, destination, kernels and border_size.
+    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[in]      weights          Weights tensor. These are 3D tensors with shape [3, 3, IFM]. Data type supported: Same as @p input.
+     * @param[in, out] input            Source tensor. Data type supported: QASYMM8/F16/F32
+     * @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           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.
      * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      */
-    ARM_COMPUTE_DEPRECATED_REL_REPLACE(19.08, NEDepthwiseConvolutionLayerOptimized)
     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(), const Size2D &dilation = Size2D(1U, 1U));
 
-    /** Static function to check if given info will lead to a valid configuration of @ref NEDepthwiseConvolutionLayer3x3
+    /** 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] weights          Weights tensor. These are 3D tensors with shape [3, 3, IFM]. Data type supported: Same as @p input.
+     * @param[in] input            Source tensor. Data type supported: QASYMM8/F16/F32
+     * @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           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.
@@ -94,61 +89,214 @@ public:
     void prepare() override;
 
 private:
-    /** Configure the kernels/functions for the generic pipeline.
+    /** Static function to choose the best depthwise convolution function for @ref NEDepthwiseConvolutionLayer
      *
-     * @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           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.
-     * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+     * @param[in] input            Source tensor info. Data type supported: QASYMM8/F16/F32
+     * @param[in] weights          Weights tensor info. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input.
+     * @param[in] biases           Biases tensor info. 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. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported.
+     * @param[in] dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      *
+     * @return a Depthwise Convolution Function
      */
-    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, const Size2D &dilation = Size2D(1U, 1U));
-    /** Configure the kernels/functions for the optimized pipeline.
+    static DepthwiseConvolutionFunction get_depthwiseconvolution_function(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(), const Size2D &dilation = Size2D(1U, 1U));
+
+    /** Basic function to execute optimized depthwise convolution routines. This function calls the following NEON kernels:
+    *
+    * @note At the moment 3x3 and 5x5 convolution of stride 1, 2 are supported
+    *
+    * -# @ref NEFillBorderKernel (if pad_x or pad_y > 0) and no assembly kernel implementation is present
+    * -# @ref NEDepthwiseConvolutionLayer3x3Kernel if 3x3 and no assembly kernel implementation is present
+    * -# @ref NEDepthwiseConvolutionAssemblyDispatch if assembly kernel implementation is present
+    * -# @ref NEDirectConvolutionLayerOutputStageKernel if re-quantization of output is required
+    * -# @ref NEActivationLayer if fused activation is required
+    *
+    */
+    class NEDepthwiseConvolutionLayerOptimizedInternal : public IFunction
+    {
+    public:
+        /** Default constructor */
+        NEDepthwiseConvolutionLayerOptimizedInternal(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+        /** Prevent instances of this class from being copied (As this class contains pointers) */
+        NEDepthwiseConvolutionLayerOptimizedInternal(const NEDepthwiseConvolutionLayerOptimizedInternal &) = delete;
+        /** Default move constructor */
+        NEDepthwiseConvolutionLayerOptimizedInternal(NEDepthwiseConvolutionLayerOptimizedInternal &&) = default;
+        /** Prevent instances of this class from being copied (As this class contains pointers) */
+        NEDepthwiseConvolutionLayerOptimizedInternal &operator=(const NEDepthwiseConvolutionLayerOptimizedInternal &) = delete;
+        /** Default move assignment operator */
+        NEDepthwiseConvolutionLayerOptimizedInternal &operator=(NEDepthwiseConvolutionLayerOptimizedInternal &&) = 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 [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.
+         * @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.
+         * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+         */
+        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(), const Size2D &dilation = Size2D(1U, 1U));
+
+        /** 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 [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.
+         * @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.
+         * @param[in] dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+         *
+         * @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(), const Size2D &dilation = Size2D(1U, 1U));
+
+        // 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 [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.
+         * @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.
+         * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+         *
+         */
+        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, const Size2D &dilation = Size2D(1U, 1U));
+        /** 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 [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.
+         * @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, const Size2D &dilation = Size2D(1U, 1U));
+        /** Run generic kernel */
+        void run_generic();
+        /** Run optimized function */
+        void run_optimized();
+
+        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 kernel:
+     *
+     * -# @ref NEDepthwiseConvolutionLayerNativeKernel
      *
-     * @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           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();
+    class NEDepthwiseConvolutionLayerGeneric : public IFunction
+    {
+    public:
+        /** Default constructor */
+        NEDepthwiseConvolutionLayerGeneric();
+        /** Prevent instances of this class from being copied (As this class contains pointers) */
+        NEDepthwiseConvolutionLayerGeneric(const NEDepthwiseConvolutionLayerGeneric &) = delete;
+        /** Default move constructor */
+        NEDepthwiseConvolutionLayerGeneric(NEDepthwiseConvolutionLayerGeneric &&) = default;
+        /** Prevent instances of this class from being copied (As this class contains pointers) */
+        NEDepthwiseConvolutionLayerGeneric &operator=(const NEDepthwiseConvolutionLayerGeneric &) = delete;
+        /** Default move assignment operator */
+        NEDepthwiseConvolutionLayerGeneric &operator=(NEDepthwiseConvolutionLayerGeneric &&) = 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           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.
+         * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+         */
+        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(), const Size2D &dilation = Size2D(1U, 1U));
 
-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;
+        /** Static function to check if given info will lead to a valid configuration of @ref NEDepthwiseConvolutionLayerGeneric
+         *
+         * @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           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.
+         * @param[in] dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+         *
+         * @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(), const Size2D &dilation = Size2D(1U, 1U));
+
+        // Inherited methods overriden:
+        void run() override;
+        void prepare() override;
+
+    private:
+        NEDepthwiseConvolutionLayerNativeKernel _depthwise_conv_kernel;
+        NEFillBorderKernel                      _fill_border;
+        NEPermute                               _permute_input;
+        NEPermute                               _permute_weights;
+        NEPermute                               _permute_output;
+        NEActivationLayer                       _activationlayer_function;
+        Tensor                                  _permuted_input;
+        Tensor                                  _permuted_weights;
+        Tensor                                  _permuted_output;
+        bool                                    _is_prepared;
+        bool                                    _is_nchw;
+        bool                                    _is_activationlayer_enabled;
+        const ITensor                          *_original_weights;
+    };
+
+    DepthwiseConvolutionFunction                 _depth_conv_func;
+    NEDepthwiseConvolutionLayerOptimizedInternal _func_optimized;
+    NEDepthwiseConvolutionLayerGeneric           _func_generic;
 };
 
 /** Basic function to execute optimized depthwise convolution routines. This function calls the following NEON kernels:
@@ -187,10 +335,11 @@ public:
      * @param[in]      act_info         (Optional) Activation layer information in case of a fused activation.
      * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      */
+    ARM_COMPUTE_DEPRECATED_REL_REPLACE(20.02, NEDepthwiseConvolutionLayer)
     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(), const Size2D &dilation = Size2D(1U, 1U));
 
-    /** Static function to check if given info will lead to a valid configuration of @ref NEDepthwiseConvolutionLayer3x3
+    /** Static function to check if given info will lead to a valid configuration of @ref NEDepthwiseConvolutionLayerOptimized
      *
      * @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 [W, H, IFM]. Data type supported: Same as @p input.
@@ -212,131 +361,7 @@ public:
     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 [W, H, 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.
-     * @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.
-     * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
-     *
-     */
-    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, const Size2D &dilation = Size2D(1U, 1U));
-    /** 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 [W, H, 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.
-     * @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, const Size2D &dilation = Size2D(1U, 1U));
-    /** 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 kernel:
- *
- * -# @ref NEDepthwiseConvolutionLayerNativeKernel
- *
- */
-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.
-     * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
-     */
-    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(), const Size2D &dilation = Size2D(1U, 1U));
-
-    /** 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.
-     * @param[in] dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
-     *
-     * @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(), const Size2D &dilation = Size2D(1U, 1U));
-
-    // Inherited methods overriden:
-    void run() override;
-    void prepare() override;
-
-private:
-    NEDepthwiseConvolutionLayerNativeKernel _depthwise_conv_kernel;
-    NEFillBorderKernel                      _fill_border;
-    NEPermute                               _permute_input;
-    NEPermute                               _permute_weights;
-    NEPermute                               _permute_output;
-    NEActivationLayer                       _activationlayer_function;
-    Tensor                                  _permuted_input;
-    Tensor                                  _permuted_weights;
-    Tensor                                  _permuted_output;
-    bool                                    _is_prepared;
-    bool                                    _is_nchw;
-    bool                                    _is_activationlayer_enabled;
-    const ITensor                          *_original_weights;
+    NEDepthwiseConvolutionLayer _func;
 };
 } // namespace arm_compute
 #endif /* __ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H__ */
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