COMPMID-3637: Move utility headers from arm_compute to src

Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: If9d6fa8c900b68c4b6fd373f2fc1f9abb83ea917
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4145
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

4 files changed, 0 insertions, 1086 deletions

diff --git a/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise.hpp b/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise.hpp
deleted file mode 100644
index 70d6689731..0000000000
--- a/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise.hpp
+++ /dev/null
@@ -1,551 +0,0 @@
-/*
- * Copyright (c) 2018-2019 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.
- */
-
-#pragma once
-
-#include <arm_neon.h>
-#include "activation.hpp"
-#include "padding.hpp"
-
-namespace depthwise
-{
-
-namespace nck = neon_convolution_kernels;
-
-class IDepthwiseConvolution
-{
-  public:
-    virtual ~IDepthwiseConvolution() = default;
-
-    virtual int output_size(
-      int dim_size,
-      unsigned int padding_before,
-      unsigned int padding_after
-    ) const = 0;
-
-    /* Set input tensor and stride. */
-    virtual void set_input(const void *inptr) = 0;
-    virtual void set_input(const void *inptr, int column_stride) = 0;
-    virtual void set_input(const void *inptr, int row_stride, int column_stride) = 0;
-    virtual void set_input(const void *inptr, int batch_stride, int row_stride, int column_stride) = 0;
-
-    /* Set output tensor and stride. */
-    virtual void set_output(void *outptr) = 0;
-    virtual void set_output(void *outptr, int column_stride) = 0;
-    virtual void set_output(void *outptr, int row_stride, int column_stride) = 0;
-    virtual void set_output(void *outptr, int batch_stride, int row_stride, int column_stride) = 0;
-
-    /* Weights and biases are re-ordered to improve memory access patterns. Use
-     * these methods to determine the size of the re-pack buffer and to set the
-     * address (and implicitly reorder the weights and biases into) the buffer.
-     */
-    virtual size_t get_packed_params_size(void) const = 0;
-    virtual void set_packed_params_buffer(void *) = 0;
-
-    virtual void pack_params(const void *weights, const void *biases=nullptr) const = 0;
-    virtual void pack_params(void *buffer, const void *weights, const void *biases=nullptr) const = 0;
-    virtual void pack_params(
-      void *buffer,
-      const void* weights,
-      unsigned int weight_row_stride,
-      unsigned int weight_col_stride,
-      const void *biases=nullptr
-    ) const = 0;
-
-    /* Working space is used to pad tensors on the fly. Before running any
-     * inference check the amount of space required, allocate and provide a
-     * pointer to the convolution engine.
-     */
-    virtual size_t get_working_space_size(unsigned int nthreads=1) const = 0;
-    virtual void set_working_space(void *) = 0;
-
-    virtual unsigned int get_window(void) const = 0;
-    virtual void run(
-      unsigned int start,
-      unsigned int stop,
-      unsigned int threadid=0
-    ) = 0;
-};
-
-template <
-  unsigned int OutputTileRows, unsigned int OutputTileCols,
-  unsigned int KernelRows, unsigned int KernelCols,
-  unsigned int StrideRows, unsigned int StrideCols,
-  typename TIn, typename TBias, typename TOut,
-  typename Derived
->
-class DepthwiseConvolutionBase : public IDepthwiseConvolution
-{
-  public:
-    // Information about the specific convolution instance
-    using InputType = TIn;
-    using BiasType = TBias;
-    using OutputType = TOut;
-    static constexpr int output_tile_rows = OutputTileRows;
-    static constexpr int output_tile_cols = OutputTileCols;
-    static constexpr int kernel_rows = KernelRows;
-    static constexpr int kernel_cols = KernelCols;
-    static constexpr int stride_rows = StrideRows;
-    static constexpr int stride_cols = StrideCols;
-    static constexpr int inner_tile_rows = stride_rows * (output_tile_rows - 1) + kernel_rows;
-    static constexpr int inner_tile_cols = stride_cols * (output_tile_cols - 1) + kernel_cols;
-
-    /** Create a new depthwise convolution engine.
-     *
-     * @param[in] n_batches Number of batches tensors.
-     * @param[in] n_input_rows Number of rows in input tensor.
-     * @param[in] n_input_cols Number of columns in input tensor.
-     * @param[in] n_channels Number of channels in input and output tensors.
-     */
-    DepthwiseConvolutionBase(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      nck::ActivationFunction activation,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-    /** Create a new depthwise convolution engine.
-     *
-     * @param[in] n_batches Number of batches tensors.
-     * @param[in] n_input_rows Number of rows in input tensor.
-     * @param[in] n_input_cols Number of columns in input tensor.
-     * @param[in] n_channels Number of channels in input and output tensors.
-     */
-    DepthwiseConvolutionBase(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      int n_output_rows, int n_output_cols,
-      nck::ActivationFunction activation,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-    // Cannot copy or move a DepthwiseConvolution.
-    DepthwiseConvolutionBase(DepthwiseConvolutionBase&) = delete;
-    DepthwiseConvolutionBase operator=(DepthwiseConvolutionBase&) = delete;
-
-    /* Set input tensor and stride. */
-    void set_input(const void *inptr) override;
-    void set_input(const void *inptr, int column_stride) override;
-    void set_input(const void *inptr, int row_stride, int column_stride) override;
-    void set_input(const void *inptr, int batch_stride, int row_stride, int column_stride) override;
-
-    /* Set output tensor and stride. */
-    void set_output(void *outptr) override;
-    void set_output(void *outptr, int column_stride) override;
-    void set_output(void *outptr, int row_stride, int column_stride) override;
-    void set_output(void *outptr, int batch_stride, int row_stride, int column_stride) override;
-
-    /** Get the number of output rows/columns.
-     *
-     * @param[in] dim_size Number of elements in the dimension (rows/columns)
-     * @param[in] same_padding True if the padding is SAME, otherwise false.
-     */
-    static int get_output_size(
-      int dim_size, unsigned int padding_before, unsigned int padding_after
-    );
-
-    int output_size(
-      int dim_size, unsigned int padding_before, unsigned int padding_after
-    ) const override;
-
-    /* Determine how much memory is required to store the packed weights and
-     * biases.
-     */
-    size_t get_packed_params_size(void) const override;
-
-    /* Set the buffer for the packed weights and biases, and perform the
-     * packing.
-     */
-    void set_packed_params_buffer(void *buffer) override;
-
-    void pack_params(const void *weights, const void *biases=nullptr) const override;
-
-    void pack_params(
-      void *buffer,
-      const void *weights,
-      const void *biases=nullptr
-    ) const override;
-
-    void pack_params(
-      void *buffer,
-      const void *weights,
-      unsigned int weight_row_stride,
-      unsigned int weight_col_stride,
-      const void *biases=nullptr
-    ) const override;
-
-    /** Query the amount of working space required.
-     * @param[in] The largest number of threads which will be used to execute
-     *            the kernel.
-     */
-    size_t get_working_space_size(unsigned int n_threads=1) const override;
-
-    /** Set the working space buffer.
-     */
-    void set_working_space(void *buffer) override;
-
-    /** Get the window of work to be performed by an instance of the operator.
-     */
-    unsigned int get_window(void) const override;
-
-    /** Perform a portion of the work associated with the operator.
-     *
-     * Will perform the window of work described by $[start, stop)$.
-     *
-     * @param[in] start Start of the window of work to perform.
-     * @param[in] stop End of the work to perform.
-     * @param[in] ID of the thread performing the work.
-     */
-    void run(
-      unsigned int start,
-      unsigned int stop,
-      unsigned int threadid=0
-    ) override;
-
-  protected:
-    /** Get the value to use to pad the tensor.
-     */
-    TIn _input_padding_value(void) const;
-
-    /** Implementation of the parameter packing.
-     */
-    void _pack_params(
-      void *buffer,
-      const void *weights,
-      unsigned int weight_row_stride,
-      unsigned int weight_col_stride,
-      const void *biases=nullptr
-    ) const;
-
-    /** Process a tile-row of the tensors.
-     */
-    void process_tile_row(
-      unsigned int threadid,
-      int n_channels,
-      const void* packed_params,
-      const InputType* inptr,
-      OutputType* outptr,
-      int row_pad_in_top,
-      int row_pad_in_left,
-      int row_pad_in_bottom,
-      int row_pad_out_bottom,
-      int n_tiles,
-      int n_input_cols,
-      int n_output_cols
-    );
-
-    /** Process a single tile of the tensor.
-     *
-     * This method will apply input/output padding (if required) and call the
-     * depthwise tile implementation.
-     */
-    void process_tile(
-      unsigned int threadid,
-      int n_channels,
-      const void* packed_params,
-      const InputType* inptr,
-      OutputType* outptr,
-      int pad_in_top,
-      int pad_in_left,
-      int pad_in_bottom,
-      int pad_in_right,
-      int pad_out_bottom,
-      int pad_out_right
-    );
-
-    /** Perform depthwise convolution on a single tile.
-     */
-    template <nck::ActivationFunction Activation>
-    void execute_tile(
-      int n_channels,
-      const void* packed_params,
-      const InputType* inptr,
-      unsigned int in_row_stride,
-      unsigned int in_col_stride,
-      OutputType* outptr,
-      unsigned int out_row_stride,
-      unsigned int out_col_stride
-    );
-
-    template <nck::ActivationFunction Activation>
-    void execute_tile(
-      int n_channels,
-      const void* packed_params,
-      const InputType* inptrs[inner_tile_rows][inner_tile_cols],
-      OutputType* outptrs[output_tile_rows][output_tile_cols]
-    );
-
-    int n_channels(void) const;
-
-  private:
-    // Member variables of instances of a convolution engine.
-    const InputType* _input;
-    OutputType* _output;
-    void* _packed_parameters;
-    void* _working_space;  // Per-thread working space
-    const int _n_batches, _n_input_rows, _n_input_cols, _n_channels,
-              _n_output_rows, _n_output_cols, _n_tile_rows, _n_tile_cols;
-    const unsigned int _padding_top, _padding_left, _padding_bottom, _padding_right;
-    const nck::ActivationFunction _activation;
-
-    // Stride information for a convolution instance
-    int _input_col_stride, _input_row_stride, _input_batch_stride;
-    int _output_col_stride, _output_row_stride, _output_batch_stride;
-
-    // Methods for getting access to working space
-    size_t _get_input_working_space_size(void) const;
-    size_t _get_output_working_space_size(void) const;
-
-    void *_get_input_working_space(unsigned int threadid) const;
-    void *_get_output_working_space(unsigned int threadid) const;
-};
-
-
-template <
-  unsigned int OutputTileRows, unsigned int OutputTileCols,
-  unsigned int KernelRows, unsigned int KernelCols,
-  unsigned int StrideRows, unsigned int StrideCols,
-  typename TIn, typename TBias, typename TOut
->
-class DepthwiseConvolution : public DepthwiseConvolutionBase<
-  OutputTileRows, OutputTileCols,
-  KernelRows, KernelCols,
-  StrideRows, StrideCols,
-  TIn, TBias, TOut,
-  DepthwiseConvolution<
-    OutputTileRows, OutputTileCols,
-    KernelRows, KernelCols,
-    StrideRows, StrideCols,
-    TIn, TBias, TOut
-  >
->
-{
-  using Base = DepthwiseConvolutionBase<
-    OutputTileRows, OutputTileCols,
-    KernelRows, KernelCols,
-    StrideRows, StrideCols,
-    TIn, TBias, TOut,
-    DepthwiseConvolution<
-      OutputTileRows, OutputTileCols,
-      KernelRows, KernelCols,
-      StrideRows, StrideCols,
-      TIn, TBias, TOut
-  > >;
-  friend Base;
-  using InputType = typename Base::InputType;
-  using OutputType = typename Base::OutputType;
-
-  public:
-    using Base::DepthwiseConvolutionBase;
-
-  protected:
-    template <nck::ActivationFunction Activation>
-    void execute_tile(
-      int n_channels,
-      const void* packed_params,
-      const TIn* inptr,
-      unsigned int in_row_stride,
-      unsigned int in_col_stride,
-      TOut* outptr,
-      unsigned int out_row_stride,
-      unsigned int out_col_stride
-    );
-
-    template <nck::ActivationFunction Activation>
-    void execute_tile(
-      int n_channels,
-      const void* packed_params,
-      const InputType* inptrs[Base::inner_tile_rows][Base::inner_tile_cols],
-      OutputType* outptrs[Base::output_tile_rows][Base::output_tile_cols]
-    );
-};
-
-
-template <
-  unsigned int OutputTileRows, unsigned int OutputTileCols,
-  unsigned int KernelRows, unsigned int KernelCols,
-  unsigned int StrideRows, unsigned int StrideCols
->
-class DepthwiseConvolution<
-  OutputTileRows, OutputTileCols,
-  KernelRows, KernelCols,
-  StrideRows, StrideCols,
-  float, float, float
-> : public DepthwiseConvolutionBase<
-  OutputTileRows, OutputTileCols,
-  KernelRows, KernelCols,
-  StrideRows, StrideCols,
-  float, float, float,
-  DepthwiseConvolution<
-    OutputTileRows, OutputTileCols,
-    KernelRows, KernelCols,
-    StrideRows, StrideCols,
-    float, float, float
-  >
->
-{
-  using Base = DepthwiseConvolutionBase<
-    OutputTileRows, OutputTileCols,
-    KernelRows, KernelCols,
-    StrideRows, StrideCols,
-    float, float, float,
-    DepthwiseConvolution<
-      OutputTileRows, OutputTileCols,
-      KernelRows, KernelCols,
-      StrideRows, StrideCols,
-      float, float, float
-  > >;
-  friend Base;
-  using InputType = typename Base::InputType;
-  using OutputType = typename Base::OutputType;
-
-  public:
-    DepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      nck::ActivationFunction activation,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-    DepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      int n_output_rows, int n_output_cols,
-      nck::ActivationFunction activation,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-  protected:
-    template <nck::ActivationFunction Activation>
-    void execute_tile(
-      int n_channels,
-      const void* packed_params,
-      const float* inptr,
-      unsigned int in_row_stride,
-      unsigned int in_col_stride,
-      float* outptr,
-      unsigned int out_row_stride,
-      unsigned int out_col_stride
-    );
-
-    template <nck::ActivationFunction Activation>
-    void execute_tile(
-      int n_channels,
-      const void* packed_params,
-      const float* inptrs[Base::inner_tile_rows][Base::inner_tile_cols],
-      float* outptrs[Base::output_tile_rows][Base::output_tile_cols]
-    );
-};
-
-#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-template <
-  unsigned int OutputTileRows, unsigned int OutputTileCols,
-  unsigned int KernelRows, unsigned int KernelCols,
-  unsigned int StrideRows, unsigned int StrideCols
->
-class DepthwiseConvolution<
-  OutputTileRows, OutputTileCols,
-  KernelRows, KernelCols,
-  StrideRows, StrideCols,
-  float16_t, float16_t, float16_t
-> : public DepthwiseConvolutionBase<
-  OutputTileRows, OutputTileCols,
-  KernelRows, KernelCols,
-  StrideRows, StrideCols,
-  float16_t, float16_t, float16_t,
-  DepthwiseConvolution<
-    OutputTileRows, OutputTileCols,
-    KernelRows, KernelCols,
-    StrideRows, StrideCols,
-    float16_t, float16_t, float16_t
-  >
->
-{
-  using Base = DepthwiseConvolutionBase<
-    OutputTileRows, OutputTileCols,
-    KernelRows, KernelCols,
-    StrideRows, StrideCols,
-    float16_t, float16_t, float16_t,
-    DepthwiseConvolution<
-      OutputTileRows, OutputTileCols,
-      KernelRows, KernelCols,
-      StrideRows, StrideCols,
-      float16_t, float16_t, float16_t
-  > >;
-  friend Base;
-  using InputType = typename Base::InputType;
-  using OutputType = typename Base::OutputType;
-
-  public:
-    DepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      nck::ActivationFunction activation,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-    DepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      int n_output_rows, int n_output_cols,
-      nck::ActivationFunction activation,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-  protected:
-    template <nck::ActivationFunction Activation>
-    void execute_tile(
-      int n_channels,
-      const void* packed_params,
-      const float16_t* inptr,
-      unsigned int in_row_stride,
-      unsigned int in_col_stride,
-      float16_t* outptr,
-      unsigned int out_row_stride,
-      unsigned int out_col_stride
-    );
-
-    template <nck::ActivationFunction Activation>
-    void execute_tile(
-      int n_channels,
-      const void* packed_params,
-      const float16_t* inptrs[Base::inner_tile_rows][Base::inner_tile_cols],
-      float16_t* outptrs[Base::output_tile_rows][Base::output_tile_cols]
-    );
-};
-#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-
-}  // namespace depthwise
diff --git a/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_dilated.hpp b/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_dilated.hpp
deleted file mode 100644
index 1bae815613..0000000000
--- a/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_dilated.hpp
+++ /dev/null
@@ -1,156 +0,0 @@
-/*
- * Copyright (c) 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.
- */
-
-#pragma once
-
-#include <deque>
-#include <functional>
-#include <memory>
-
-#include "depthwise.hpp"
-
-namespace depthwise
-{
-
-template <
-  unsigned int OutputTileRows, unsigned int OutputTileCols,
-  unsigned int KernelRows, unsigned int KernelCols,
-  unsigned int StrideRows, unsigned int StrideCols,
-  typename TIn, typename TBias, typename TOut
->
-class DilatedDepthwiseConvolution : public IDepthwiseConvolution
-{
-  public:
-    /** Create a new dilated depthwise convolution engine.
-     */
-    DilatedDepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      int dilation_factor,
-      nck::ActivationFunction activation,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-    /** Create a new dilated depthwise convolution engine.
-     */
-    DilatedDepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      int dilation_factor, int n_output_rows, int n_output_cols,
-      nck::ActivationFunction activation,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-    // Cannot copy or move a DilatedDepthwiseConvolution.
-    DilatedDepthwiseConvolution(DilatedDepthwiseConvolution&) = delete;
-    DilatedDepthwiseConvolution operator=(DilatedDepthwiseConvolution&) = delete;
-
-    /* Set input tensor and stride. */
-    void set_input(const void *inptr) override;
-    void set_input(const void *inptr, int column_stride) override;
-    void set_input(const void *inptr, int row_stride, int column_stride) override;
-    void set_input(const void *inptr, int batch_stride, int row_stride, int column_stride) override;
-
-    /* Set output tensor and stride. */
-    void set_output(void *outptr) override;
-    void set_output(void *outptr, int column_stride) override;
-    void set_output(void *outptr, int row_stride, int column_stride) override;
-    void set_output(void *outptr, int batch_stride, int row_stride, int column_stride) override;
-
-    static int get_output_size(
-      int dim_size,
-      unsigned int padding_before,
-      unsigned int padding_after,
-      int dilation_factor
-    );
-
-    int output_size(
-      int dim_size, unsigned int padding_before, unsigned int padding_after
-    ) const override;
-
-    /* Weights and biases are re-ordered to improve memory access patterns. Use
-     * these methods to determine the size of the re-pack buffer and to set the
-     * address (and implicitly reorder the weights and biases into) the buffer.
-     */
-    size_t get_packed_params_size(void) const override;
-    void set_packed_params_buffer(void *) override;
-
-    void pack_params(const void *weights, const void *biases=nullptr) const override;
-    void pack_params(void *buffer, const void *weights, const void *biases=nullptr) const override;
-    void pack_params(
-      void *buffer,
-      const void* weights,
-      unsigned int weight_row_stride,
-      unsigned int weight_col_stride,
-      const void *biases=nullptr
-    ) const override;
-
-    /* Working space is used to pad tensors on the fly. Before running any
-     * inference check the amount of space required, allocate and provide a
-     * pointer to the convolution engine.
-     */
-    size_t get_working_space_size(unsigned int nthreads=1) const override;
-    void set_working_space(void *) override;
-
-    unsigned int get_window(void) const override;
-    void run(unsigned int start, unsigned int stop, unsigned int threadid=0) override;
-
-  protected:
-    /** Protected constructor which also accepts a function to construct a new
-     * subconvolution
-     */
-    DilatedDepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      int dilation_factor, int n_output_rows, int n_output_cols,
-      nck::ActivationFunction activation,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right,
-      std::function<IDepthwiseConvolution *(int, int, int, int, int, int, nck::ActivationFunction, unsigned int, unsigned int, unsigned int, unsigned int)> subconvfn
-    );
-
-    const int _dilation_factor;
-    const int _n_input_rows, _n_input_cols, _n_channels;
-    const int _padding_top, _padding_left;
-    const int _n_output_rows, _n_output_cols;
-
-    /* Dilated depthwise convolution is performed through repeated calls to
-     * non-dilated convolutions. If the dilation factor is $n$, then we perform
-     * $(n + 1)^2$ depthwise convolutions.
-     */
-    using BaseDepthwise = DepthwiseConvolution<
-      OutputTileRows, OutputTileCols,
-      KernelRows, KernelCols,
-      StrideRows, StrideCols,
-      TIn, TBias, TOut
-    >;
-    std::deque<std::deque<std::unique_ptr<IDepthwiseConvolution>>> _convs;
-};
-
-}  // namespace depthwise
diff --git a/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp b/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp
deleted file mode 100644
index 4343f6ad45..0000000000
--- a/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp
+++ /dev/null
@@ -1,291 +0,0 @@
-/*
- * Copyright (c) 2018-2019 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.
- */
-
-#pragma once
-#include "depthwise.hpp"
-#include "qasymm8.hpp"
-#include "qsymm8.hpp"
-#pragma once
-
-using namespace neon_convolution_kernels;
-using namespace qasymm8;
-
-inline int32x4_t saturating_doubling_high_mul(const int32x4_t& a, const int32x4_t& b)
-{
-  return vqrdmulhq_s32(a, b);
-}
-
-inline int32x4_t saturating_doubling_high_mul(const int32x4_t& a, const int32_t& b)
-{
-  return vqrdmulhq_n_s32(a, b);
-}
-
-inline int32_t saturating_doubling_high_mul(const int32_t& a, const int32_t& b)
-{
-  return vget_lane_s32(vqrdmulh_n_s32(vdup_n_s32(a), b), 0);
-}
-
-inline int32x4_t rounding_divide_by_exp2(const int32x4_t& x, const int32x4_t shift)
-{
-  const int32x4_t fixup = vshrq_n_s32(vandq_s32(x, shift), 31);
-  const int32x4_t fixed = vqaddq_s32(x, fixup);
-  return vrshlq_s32(fixed, shift);
-}
-
-inline int32x4_t rounding_divide_by_exp2(const int32x4_t& x, const int exponent)
-{
-  const int32x4_t shift = vdupq_n_s32(-exponent);
-  const int32x4_t fixup = vshrq_n_s32(vandq_s32(x, shift), 31);
-  const int32x4_t fixed = vqaddq_s32(x, fixup);
-  return vrshlq_s32(fixed, shift);
-}
-
-inline int32x2_t rounding_divide_by_exp2(const int32x2_t& x, const int exponent)
-{
-  const int32x2_t shift = vdup_n_s32(-exponent);
-  const int32x2_t fixup = vshr_n_s32(vand_s32(x, shift), 31);
-  const int32x2_t fixed = vqadd_s32(x, fixup);
-  return vrshl_s32(fixed, shift);
-}
-
-inline int32_t rounding_divide_by_exp2(const int32_t& x, const int exponent)
-{
-  const int32x2_t xs = vdup_n_s32(x);
-  return vget_lane_s32(rounding_divide_by_exp2(xs, exponent), 0);
-}
-
-namespace depthwise
-{
-
-namespace nck = neon_convolution_kernels;
-
-template <
-  unsigned int OutputTileRows, unsigned int OutputTileCols,
-  unsigned int KernelRows, unsigned int KernelCols,
-  unsigned int StrideRows, unsigned int StrideCols
->
-class QAsymm8DepthwiseConvolution : public DepthwiseConvolutionBase<
-  OutputTileRows, OutputTileCols,
-  KernelRows, KernelCols,
-  StrideRows, StrideCols,
-  uint8_t, int32_t, uint8_t,
-  QAsymm8DepthwiseConvolution<OutputTileRows, OutputTileCols, KernelRows, KernelCols, StrideRows, StrideCols>
->
-{
-  using Base = DepthwiseConvolutionBase<
-    OutputTileRows, OutputTileCols,
-    KernelRows, KernelCols,
-    StrideRows, StrideCols,
-    uint8_t, int32_t, uint8_t,
-    QAsymm8DepthwiseConvolution<OutputTileRows, OutputTileCols, KernelRows, KernelCols, StrideRows, StrideCols>
-  >;
-  friend Base;
-  using InputType = typename Base::InputType;
-  using OutputType = typename Base::OutputType;
-
-  public:
-    QAsymm8DepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      nck::ActivationFunction activation,
-      const qasymm8::QAsymm8Params& weight_quantisation,
-      const qasymm8::QAsymm8Params& input_quantisation,
-      const qasymm8::QAsymm8Params& output_quantisation,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-    QAsymm8DepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      int n_output_rows, int n_output_cols,
-      nck::ActivationFunction activation,
-      const qasymm8::QAsymm8Params& weight_quantisation,
-      const qasymm8::QAsymm8Params& input_quantisation,
-      const qasymm8::QAsymm8Params& output_quantisation,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-    QAsymm8DepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      nck::ActivationFunction activation,
-      const qasymm8::QAsymm8Params& weight_quantisation,
-      const qasymm8::QAsymm8Params& input_quantisation,
-      const qasymm8::QAsymm8Params& output_quantisation,
-      const qasymm8::QAsymm8RescaleParams& rescale_parameters,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-    QAsymm8DepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      int n_output_rows, int n_output_cols,
-      nck::ActivationFunction activation,
-      const qasymm8::QAsymm8Params& weight_quantisation,
-      const qasymm8::QAsymm8Params& input_quantisation,
-      const qasymm8::QAsymm8Params& output_quantisation,
-      const qasymm8::QAsymm8RescaleParams& rescale_parameters,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-  protected:
-    uint8_t _input_padding_value(void) const;
-
-    void _pack_params(
-      void *buffer,
-      const void *weights,
-      unsigned int weight_row_stride,
-      unsigned int weight_col_stride,
-      const void *biases=nullptr
-    ) const;
-
-    template <nck::ActivationFunction Activation>
-    void execute_tile(
-      int n_channels,
-      const void* packed_params,
-      const uint8_t* inptr,
-      unsigned int in_row_stride,
-      unsigned int in_col_stride,
-      uint8_t* outptr,
-      unsigned int out_row_stride,
-      unsigned int out_col_stride
-    );
-
-    template <nck::ActivationFunction Activation>
-    void execute_tile(
-      int n_channels,
-      const void* packed_params,
-      const uint8_t* inptrs[Base::inner_tile_rows][Base::inner_tile_cols],
-      uint8_t* outptrs[Base::output_tile_rows][Base::output_tile_cols]
-    );
-
-  private:
-    // Quantization parameters
-    const qasymm8::QAsymm8Params _weights_quant, _inputs_quant, _output_quant;
-    const qasymm8::QAsymm8RescaleParams rescale_parameters;
-};
-
-template <
-  unsigned int OutputTileRows, unsigned int OutputTileCols,
-  unsigned int KernelRows, unsigned int KernelCols,
-  unsigned int StrideRows, unsigned int StrideCols
->
-class QSymm8HybridPerChannelDepthwiseConvolution : public DepthwiseConvolutionBase<
-  OutputTileRows, OutputTileCols,
-  KernelRows, KernelCols,
-  StrideRows, StrideCols,
-  uint8_t, int32_t, uint8_t,
-  QSymm8HybridPerChannelDepthwiseConvolution<OutputTileRows, OutputTileCols, KernelRows, KernelCols, StrideRows, StrideCols>
->
-{
-  using Base = DepthwiseConvolutionBase<
-    OutputTileRows, OutputTileCols,
-    KernelRows, KernelCols,
-    StrideRows, StrideCols,
-    uint8_t, int32_t, uint8_t,
-    QSymm8HybridPerChannelDepthwiseConvolution<OutputTileRows, OutputTileCols, KernelRows, KernelCols, StrideRows, StrideCols>
-  >;
-  friend Base;
-  using InputType = typename Base::InputType;
-  using OutputType = typename Base::OutputType;
-
-  public:
-  QSymm8HybridPerChannelDepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      nck::ActivationFunction activation,
-      const qsymm8::QSymm8PerChannelParams& weight_quantisation,
-      const qasymm8::QAsymm8Params& input_quantisation,
-      const qasymm8::QAsymm8Params& output_quantisation,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-  QSymm8HybridPerChannelDepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      nck::ActivationFunction activation,
-      const qsymm8::QSymm8PerChannelParams& weight_quantisation,
-      const qasymm8::QAsymm8Params& input_quantisation,
-      const qasymm8::QAsymm8Params& output_quantisation,
-      const qsymm8::QSymm8PerChannelRescaleParams& rescale_parameters,
-      unsigned int padding_top,
-      unsigned int padding_left,
-      unsigned int padding_bottom,
-      unsigned int padding_right
-    );
-
-  size_t get_packed_params_size(void) const override
-  {
-      return this->n_channels() * (sizeof(int8_t)*KernelRows*KernelCols + 3*sizeof(int32_t));
-
-  }
-
-  protected:
-    uint8_t _input_padding_value(void) const;
-
-    void _pack_params(
-      void *buffer,
-      const void *weights,
-      unsigned int weight_row_stride,
-      unsigned int weight_col_stride,
-      const void *biases=nullptr
-    ) const;
-
-    template <nck::ActivationFunction Activation>
-    void execute_tile(
-      int n_channels,
-      const void* packed_params,
-      const uint8_t* inptr,
-      unsigned int in_row_stride,
-      unsigned int in_col_stride,
-      uint8_t* outptr,
-      unsigned int out_row_stride,
-      unsigned int out_col_stride
-    );
-
-    template <nck::ActivationFunction Activation>
-    void execute_tile(
-      int n_channels,
-      const void* packed_params,
-      const uint8_t* inptrs[Base::inner_tile_rows][Base::inner_tile_cols],
-      uint8_t* outptrs[Base::output_tile_rows][Base::output_tile_cols]
-    );
-
-  private:
-    // Quantization parameters
-    const qsymm8::QSymm8PerChannelParams _weights_quant;
-    const qasymm8::QAsymm8Params _input_quant, _output_quant;
-    const qsymm8::QSymm8PerChannelRescaleParams _rescale_parameters;
-};
-
-}  // namespace depthwise
diff --git a/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized_dilated.hpp b/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized_dilated.hpp
deleted file mode 100644
index a11b0981c9..0000000000
--- a/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized_dilated.hpp
+++ /dev/null
@@ -1,88 +0,0 @@
-/*
- * Copyright (c) 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.
- */
-
-#pragma once
-#include "depthwise_dilated.hpp"
-#include "depthwise_quantized.hpp"
-
-namespace depthwise {
-
-template <unsigned int OutputTileRows, unsigned int OutputTileCols,
-          unsigned int KernelRows, unsigned int KernelCols,
-          unsigned int StrideRows, unsigned int StrideCols>
-class QAsymm8DilatedDepthwiseConvolution
-    : public DilatedDepthwiseConvolution<
-          OutputTileRows, OutputTileCols, KernelRows, KernelCols, StrideRows,
-          StrideCols, uint8_t, int32_t, uint8_t> {
-public:
-  /** Create a new dilated depthwise convolution engine.
-   */
-  QAsymm8DilatedDepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      int dilation_factor, nck::ActivationFunction activation,
-      const qasymm8::QAsymm8Params &weight_quantisation,
-      const qasymm8::QAsymm8Params &input_quantisation,
-      const qasymm8::QAsymm8Params &output_quantisation,
-      unsigned int padding_top, unsigned int padding_left,
-      unsigned int padding_bottom, unsigned int padding_right);
-
-  /** Create a new dilated depthwise convolution engine.
-   */
-  QAsymm8DilatedDepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      int dilation_factor, int n_output_rows, int n_output_cols,
-      nck::ActivationFunction activation,
-      const qasymm8::QAsymm8Params &weight_quantisation,
-      const qasymm8::QAsymm8Params &input_quantisation,
-      const qasymm8::QAsymm8Params &output_quantisation,
-      unsigned int padding_top, unsigned int padding_left,
-      unsigned int padding_bottom, unsigned int padding_right);
-
-  /** Create a new dilated depthwise convolution engine.
-   */
-  QAsymm8DilatedDepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      int dilation_factor, nck::ActivationFunction activation,
-      const qasymm8::QAsymm8Params &weight_quantisation,
-      const qasymm8::QAsymm8Params &input_quantisation,
-      const qasymm8::QAsymm8Params &output_quantisation,
-      const qasymm8::QAsymm8RescaleParams &rescale_parameters,
-      unsigned int padding_top, unsigned int padding_left,
-      unsigned int padding_bottom, unsigned int padding_right);
-
-  /** Create a new dilated depthwise convolution engine.
-   */
-  QAsymm8DilatedDepthwiseConvolution(
-      int n_batches, int n_input_rows, int n_input_cols, int n_channels,
-      int dilation_factor, int n_output_rows, int n_output_cols,
-      nck::ActivationFunction activation,
-      const qasymm8::QAsymm8Params &weight_quantisation,
-      const qasymm8::QAsymm8Params &input_quantisation,
-      const qasymm8::QAsymm8Params &output_quantisation,
-      const qasymm8::QAsymm8RescaleParams& rescale_parameters,
-      unsigned int padding_top, unsigned int padding_left,
-      unsigned int padding_bottom, unsigned int padding_right);
-};
-
-}  // namespace depthwise