text: /*
   * Copyright (c) 2021 Arm Limited.
   *
   * SPDX-License-Identifier: MIT
   *
   * Permission is hereby granted, free of charge, to any person obtaining a copy
   * of this software and associated documentation files (the "Software"), to
   * deal in the Software without restriction, including without limitation the
   * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
   * sell copies of the Software, and to permit persons to whom the Software is
   * furnished to do so, subject to the following conditions:
   *
   * The above copyright notice and this permission notice shall be included in all
   * copies or substantial portions of the Software.
   *
   * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
   * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
   * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
   * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
   * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
   * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
   * SOFTWARE.
   */
  #ifndef SRC_CORE_NEON_KERNELS_CONV3D_QUANTIZED_H
  #define SRC_CORE_NEON_KERNELS_CONV3D_QUANTIZED_H
  
  #include "arm_compute/core/Types.h"
  #include "arm_compute/core/utils/misc/Traits.h"
  #include "arm_compute/core/utils/quantization/AsymmHelpers.h"
  #include "arm_compute/runtime/FunctionDescriptors.h"
  #include "src/core/NEON/NEAsymm.h"
  #include "src/core/NEON/wrapper/wrapper.h"
  #include "src/core/helpers/WindowHelpers.h"
  
  namespace arm_compute
  {
  namespace cpu
  {
  template <typename T>
  void directconv3d_quantized_neon_ndhwc(const ITensor *src0, const ITensor *src1, const ITensor *src2, ITensor *dst, const Conv3dInfo &conv_info, const Window &window)
  {
      const ITensor *src     = src0;
      const ITensor *weights = src1;
      const ITensor *biases  = src2;
  
      using vtype                                = wrapper::traits::neon_bitvector<T, wrapper::traits::BitWidth::W128>;
      using vector_type                          = typename vtype::type;
      using tag_type                             = typename vtype::tag_type;
      constexpr int num_elems_read_per_iteration = 16 / sizeof(T);
      using q16_t                                = typename wrapper::traits::promote_t<T>;
      using q32_t                                = typename wrapper::traits::promote_t<q16_t>;
      using q32x4_t                              = typename wrapper::traits::neon_vector<q32_t, 4>::type;
  
      const int32_t input_offset   = -src->info()->quantization_info().uniform().offset;
      const float   input_scale    = src->info()->quantization_info().uniform().scale;
      const int32_t weights_offset = -weights->info()->quantization_info().uniform().offset;
      const float   weights_scale  = weights->info()->quantization_info().uniform().scale;
      const int32_t output_offset  = dst->info()->quantization_info().uniform().offset;
      const float   output_scale   = dst->info()->quantization_info().uniform().scale;
  
      int32_t     output_multiplier = 0;
      int32_t     output_shift      = 0;
      const float multiplier        = input_scale * weights_scale / output_scale;
      arm_compute::quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift);
  
      // Scalar quantities (N D H W Cin)
      const int element_size   = src->info()->element_size();
      const int input_stride_w = src->info()->strides_in_bytes().y() / element_size;
      const int input_stride_h = src->info()->strides_in_bytes().z() / element_size;
      const int input_stride_d = src->info()->strides_in_bytes()[3] / element_size;
      const int input_stride_n = src->info()->strides_in_bytes()[4] / element_size;
      const int input_dim_w    = src->info()->dimension(1);
      const int input_dim_h    = src->info()->dimension(2);
      const int input_dim_d    = src->info()->dimension(3);
  
      // Kernel info (D H W Cin Cout)
      const unsigned int kernel_stride_w = weights->info()->strides_in_bytes()[2] / element_size;
      const unsigned int kernel_stride_h = weights->info()->strides_in_bytes()[3] / element_size;
      const unsigned int kernel_stride_d = weights->info()->strides_in_bytes()[4] / element_size;
      const int          kernel_dim_w    = weights->info()->dimension(2);
      const int          kernel_dim_h    = weights->info()->dimension(3);
      const int          kernel_dim_d    = weights->info()->dimension(4);
  
      // Convolution padding and stride
      const int conv_pad_top   = conv_info.padding.top;
      const int conv_pad_left  = conv_info.padding.left;
      const int conv_pad_front = conv_info.padding.front;
      const int conv_stride_w  = conv_info.stride.width;
      const int conv_stride_h  = conv_info.stride.height;
      const int conv_stride_d  = conv_info.stride.depth;
  
      // Setup input window for the output iterator
      Window window_out = window;
      window_out.set(Window::DimX, Window::Dimension(0, 1, 1));
  
      // Setup input window for the weights iterator
      Window window_w = calculate_max_window(*weights->info(), Steps());
      window_w.set(Window::DimY, Window::Dimension(0, 1, 1));
      window_w.set(Window::DimZ, Window::Dimension(0, 1, 1));
      window_w.set(Window::DimW, Window::Dimension(0, 1, 1));
      window_w.set(4, Window::Dimension(0, 1, 1));
  
      Iterator out(dst, window_out);
      Iterator wei(weights, window_w);
  
      const int32_t *biases_ptr = nullptr;
      if(biases != nullptr)
      {
          biases_ptr = reinterpret_cast<int32_t *>(biases->buffer() + biases->info()->offset_first_element_in_bytes());
      }
      execute_window_loop(window_out, [&](const Coordinates & id)
      {
          // We are computing the theoretical input starting points
          const int in_w_start_t = static_cast<int>(id.y()) * conv_stride_w - conv_pad_left;
          const int in_h_start_t = static_cast<int>(id.z()) * conv_stride_h - conv_pad_top;
          const int in_d_start_t = static_cast<int>(id[3]) * conv_stride_d - conv_pad_front;
          const int in_w_end_t   = in_w_start_t + kernel_dim_w;
          const int in_h_end_t   = in_h_start_t + kernel_dim_h;
          const int in_d_end_t   = in_d_start_t + kernel_dim_d;
  
          // We are computing the valid initial and ending input points by checking the borders
          const int in_w_start = std::max(in_w_start_t, 0);
          const int in_h_start = std::max(in_h_start_t, 0);
          const int in_d_start = std::max(in_d_start_t, 0);
          const int in_w_end   = std::min(in_w_end_t, input_dim_w);
          const int in_h_end   = std::min(in_h_end_t, input_dim_h);
          const int in_d_end   = std::min(in_d_end_t, input_dim_d);
  
          // We use the input points to select the valid weight points to use
          const int wei_w_start = in_w_start - in_w_start_t;
          const int wei_h_start = in_h_start - in_h_start_t;
          const int wei_d_start = in_d_start - in_d_start_t;
          const int wei_w_end   = kernel_dim_w - (in_w_end_t - in_w_end);
          const int wei_h_end   = kernel_dim_h - (in_h_end_t - in_h_end);
          const int wei_d_end   = kernel_dim_d - (in_d_end_t - in_d_end);
  
          const int      index_c_out_end = weights->info()->dimension(0);
          const int      index_c_in_end  = weights->info()->dimension(1);
          const T *const in_ptr_start    = reinterpret_cast<const T *>(src->buffer() + src->info()->offset_first_element_in_bytes()) + id[4] * input_stride_n;
  
          execute_window_loop(window_w, [&](const Coordinates & id_w)
          {
              /*
              * This is the loop in the weights, and it goes along OFM (output feature map)
              */
              const auto weights_ptr_start = reinterpret_cast<const T *>(wei.ptr());
              int32_t    acc               = static_cast<int32_t>(0);
              T         *out_ptr           = reinterpret_cast<T *>(out.ptr());
              for(int index_wei_d = wei_d_start, index_in_d = in_d_start; index_wei_d < wei_d_end; ++index_wei_d, ++index_in_d)
              {
                  const auto in_ptr_d      = in_ptr_start + index_in_d * input_stride_d;
                  const auto weights_ptr_d = weights_ptr_start + index_wei_d * kernel_stride_d;
                  for(int index_wei_h = wei_h_start, index_in_h = in_h_start; index_wei_h < wei_h_end; ++index_wei_h, ++index_in_h)
                  {
                      const T *const in_ptr_row      = in_ptr_d + index_in_h * input_stride_h;
                      const T *const weights_ptr_row = weights_ptr_d + index_wei_h * kernel_stride_h;
                      for(int index_wei_w = wei_w_start, index_in_w = in_w_start; index_wei_w < wei_w_end; ++index_wei_w, ++index_in_w)
                      {
                          const T    *in_ptr_mover      = in_ptr_row + index_in_w * input_stride_w;
                          const T    *weights_ptr_mover = weights_ptr_row + index_wei_w * kernel_stride_w;
                          int         index_c_in        = 0;
                          vector_type w_vec             = wrapper::vdup_n(static_cast<T>(0), tag_type());
  
                          q32x4_t acc_q32_0 = wrapper::vdup_n(static_cast<q32_t>(0), tag_type());
                          q32x4_t acc_q32_1 = wrapper::vdup_n(static_cast<q32_t>(0), tag_type());
                          q32x4_t acc_q32_2 = wrapper::vdup_n(static_cast<q32_t>(0), tag_type());
                          q32x4_t acc_q32_3 = wrapper::vdup_n(static_cast<q32_t>(0), tag_type());
  
                          for(; index_c_in <= index_c_in_end - num_elems_read_per_iteration;
                              index_c_in += num_elems_read_per_iteration, in_ptr_mover += num_elems_read_per_iteration)
                          {
                              const auto src_vec = wrapper::vloadq(in_ptr_mover);
                              //Load Cin weights
                              for(unsigned int k = 0; k < num_elems_read_per_iteration; ++k, weights_ptr_mover += index_c_out_end)
                              {
                                  w_vec = wrapper::vsetlane(*weights_ptr_mover, w_vec, k);
                              }
                              q32x4_t src_q32_0 = wrapper::vdup_n(static_cast<q32_t>(input_offset), tag_type());
                              q32x4_t src_q32_1 = wrapper::vdup_n(static_cast<q32_t>(input_offset), tag_type());
                              q32x4_t src_q32_2 = wrapper::vdup_n(static_cast<q32_t>(input_offset), tag_type());
                              q32x4_t src_q32_3 = wrapper::vdup_n(static_cast<q32_t>(input_offset), tag_type());
  
                              q32x4_t wei_q32_0 = wrapper::vdup_n(static_cast<q32_t>(weights_offset), tag_type());
                              q32x4_t wei_q32_1 = wrapper::vdup_n(static_cast<q32_t>(weights_offset), tag_type());
                              q32x4_t wei_q32_2 = wrapper::vdup_n(static_cast<q32_t>(weights_offset), tag_type());
                              q32x4_t wei_q32_3 = wrapper::vdup_n(static_cast<q32_t>(weights_offset), tag_type());
  
                              const auto src_q16_0 = wrapper::vmovl(wrapper::vgetlow(src_vec));
                              const auto src_q16_1 = wrapper::vmovl(wrapper::vgethigh(src_vec));
                              const auto wei_q16_0 = wrapper::vmovl(wrapper::vgetlow(w_vec));
                              const auto wei_q16_1 = wrapper::vmovl(wrapper::vgethigh(w_vec));
  
                              src_q32_0 = wrapper::vadd(src_q32_0, wrapper::vmovl(wrapper::vgetlow(src_q16_0)));
                              src_q32_1 = wrapper::vadd(src_q32_1, wrapper::vmovl(wrapper::vgethigh(src_q16_0)));
                              src_q32_2 = wrapper::vadd(src_q32_2, wrapper::vmovl(wrapper::vgetlow(src_q16_1)));
                              src_q32_3 = wrapper::vadd(src_q32_3, wrapper::vmovl(wrapper::vgethigh(src_q16_1)));
  
                              wei_q32_0 = wrapper::vadd(wei_q32_0, wrapper::vmovl(wrapper::vgetlow(wei_q16_0)));
                              wei_q32_1 = wrapper::vadd(wei_q32_1, wrapper::vmovl(wrapper::vgethigh(wei_q16_0)));
                              wei_q32_2 = wrapper::vadd(wei_q32_2, wrapper::vmovl(wrapper::vgetlow(wei_q16_1)));
                              wei_q32_3 = wrapper::vadd(wei_q32_3, wrapper::vmovl(wrapper::vgethigh(wei_q16_1)));
  
                              acc_q32_0 = wrapper::vmla(acc_q32_0, wei_q32_0, src_q32_0);
                              acc_q32_1 = wrapper::vmla(acc_q32_1, wei_q32_1, src_q32_1);
                              acc_q32_2 = wrapper::vmla(acc_q32_2, wei_q32_2, src_q32_2);
                              acc_q32_3 = wrapper::vmla(acc_q32_3, wei_q32_3, src_q32_3);
                          }
  #if defined(__aarch64__)
                          acc += wrapper::vaddv(acc_q32_0);
                          acc += wrapper::vaddv(acc_q32_1);
                          acc += wrapper::vaddv(acc_q32_2);
                          acc += wrapper::vaddv(acc_q32_3);
  #else // __aarch64__
                          auto temp = wrapper::vpadd(wrapper::vgethigh(acc_q32_0), wrapper::vgetlow(acc_q32_0));
                          temp      = wrapper::vpadd(temp, temp);
                          acc       += wrapper::vgetlane(temp, 0);
  
                          temp      = wrapper::vpadd(wrapper::vgethigh(acc_q32_1), wrapper::vgetlow(acc_q32_1));
                          temp      = wrapper::vpadd(temp, temp);
                          acc       += wrapper::vgetlane(temp, 0);
  
                          temp      = wrapper::vpadd(wrapper::vgethigh(acc_q32_2), wrapper::vgetlow(acc_q32_2));
                          temp      = wrapper::vpadd(temp, temp);
                          acc       += wrapper::vgetlane(temp, 0);
  
                          temp      = wrapper::vpadd(wrapper::vgethigh(acc_q32_3), wrapper::vgetlow(acc_q32_3));
                          temp      = wrapper::vpadd(temp, temp);
                          acc       += wrapper::vgetlane(temp, 0);
  
  #endif // __aarch64__
  
                          for(; index_c_in < index_c_in_end; ++index_c_in, ++in_ptr_mover, weights_ptr_mover += index_c_out_end)
                          {
                              const auto src_val = *(in_ptr_mover) + input_offset;
                              const auto w_val   = *(weights_ptr_mover) + weights_offset;
                              acc += src_val * w_val;
                          }
                      }
                  }
              }
  
              if(biases)
              {
                  acc += *reinterpret_cast<const int32_t *>(biases_ptr + id_w[0]);
              }
  
              T out_val                                   = finalize_quantization(acc, output_multiplier, output_shift, output_offset, T(0), T(0), false);
              *(reinterpret_cast<T *>(out_ptr + id_w[0])) = out_val;
          },
          wei);
      },
      out);
  }
  } // namespace cpu
  } // namespace arm_compute
  #endif // SRC_CORE_NEON_KERNELS_CONV3D_QUANTIZED_H