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, 1086 insertions, 0 deletions

diff --git a/src/core/NEON/kernels/convolution/depthwise/depthwise.hpp b/src/core/NEON/kernels/convolution/depthwise/depthwise.hpp
new file mode 100644
index 0000000000..70d6689731
--- /dev/null
+++ b/src/core/NEON/kernels/convolution/depthwise/depthwise.hpp
@@ -0,0 +1,551 @@
+/*
+ * 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/src/core/NEON/kernels/convolution/depthwise/depthwise_dilated.hpp b/src/core/NEON/kernels/convolution/depthwise/depthwise_dilated.hpp
new file mode 100644
index 0000000000..1bae815613
--- /dev/null
+++ b/src/core/NEON/kernels/convolution/depthwise/depthwise_dilated.hpp
@@ -0,0 +1,156 @@
+/*
+ * 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/src/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp b/src/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp
new file mode 100644
index 0000000000..4343f6ad45
--- /dev/null
+++ b/src/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp
@@ -0,0 +1,291 @@
+/*
+ * 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/src/core/NEON/kernels/convolution/depthwise/depthwise_quantized_dilated.hpp b/src/core/NEON/kernels/convolution/depthwise/depthwise_quantized_dilated.hpp
new file mode 100644
index 0000000000..a11b0981c9
--- /dev/null
+++ b/src/core/NEON/kernels/convolution/depthwise/depthwise_quantized_dilated.hpp
@@ -0,0 +1,88 @@
+/*
+ * 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