1 files changed, 156 insertions, 0 deletions
diff --git a/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp b/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp
index f8db4db6cc..ef3adc4c0c 100644
--- a/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp
+++ b/arm_compute/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp
@@ -25,6 +25,68 @@
 #pragma once
 #include "depthwise.hpp"
 #include "qasymm8.hpp"
+#include "qsymm8.hpp"
+#pragma once
+
+using namespace neon_convolution_kernels;
+using namespace qasymm8;
+
+template <typename T, typename U = int32_t>
+inline T saturating_doubling_high_mul(const T&, const U&);
+
+template <>
+inline int32x4_t saturating_doubling_high_mul(const int32x4_t& a, const int32x4_t& b)
+{
+  return vqrdmulhq_s32(a, b);
+}
+
+template <>
+inline int32x4_t saturating_doubling_high_mul(const int32x4_t& a, const int32_t& b)
+{
+  return vqrdmulhq_n_s32(a, b);
+}
+
+template <>
+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);
+}
+
+template <typename T, typename U = int32_t>
+inline T rounding_divide_by_exp2(const T& x, const U exponent);
+
+template <>
+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);
+}
+
+template <>
+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);
+}
+
+template <>
+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);
+}
+
+template <>
+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
 {
@@ -145,4 +207,98 @@ class QAsymm8DepthwiseConvolution : public DepthwiseConvolutionBase<
     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