text: /**
   * \file dnn/src/naive/argmxx/opr_impl.cpp
   * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
   *
   * Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
   *
   * Unless required by applicable law or agreed to in writing,
   * software distributed under the License is distributed on an
   * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   */
  #include "src/naive/argmxx/opr_impl.h"
  
  #include "src/common/reduce_helper.h"
  #include "src/common/utils.h"
  #include "src/naive/handle.h"
  
  #include <numeric>
  
  namespace {
  
  using namespace megdnn;
  
  template <bool is_max>
  struct traits;
  
  template <>
  struct traits<true> {
      static const float init;
      static bool better_than(float lhs, float rhs) { return lhs > rhs; }
  };
  const float traits<true>::init = std::numeric_limits<float>::lowest();
  
  template <>
  struct traits<false> {
      static const float init;
      static float better_than(float lhs, float rhs) { return lhs < rhs; }
  };
  const float traits<false>::init = std::numeric_limits<float>::max();
  
  template <typename T, bool is_max>
  void exec_forward(
          _megdnn_tensor_in src, _megdnn_tensor_out dst, const ArgmxxBase::Param& param) {
      size_t A, B, C;
      reduce::get_ABC(src.layout, A, B, C, param.axis);
      for (size_t a = 0; a < A; ++a)
          for (size_t c = 0; c < C; ++c) {
              float best_val = traits<is_max>::init;
              size_t best_arg = 0;
              for (size_t b = 0; b < B; ++b) {
                  float curr_val = float(src.ptr<T>()[(a * B + b) * C + c]);
                  if (traits<is_max>::better_than(curr_val, best_val)) {
                      best_val = curr_val;
                      best_arg = b;
                  }
              }
              dst.ptr<dt_int32>()[a * C + c] = best_arg;
          }
  }
  
  }  // anonymous namespace
  
  namespace megdnn {
  namespace naive {
  
  void ArgmaxForwardImpl::exec(
          _megdnn_tensor_in src, _megdnn_tensor_out dst, _megdnn_workspace workspace) {
      check_exec(src.layout, dst.layout, workspace.size);
  #define cb(DType)                                                          \
      if (src.layout.dtype.enumv() == DTypeTrait<DType>::enumv) {            \
          using ctype = typename DTypeTrait<DType>::ctype;                   \
          MEGDNN_DISPATCH_CPU_KERN(                                          \
                  static_cast<HandleImpl*>(handle()),                        \
                  exec_forward<ctype MEGDNN_COMMA true>(src, dst, param())); \
      }
      MEGDNN_FOREACH_COMPUTING_DTYPE(cb)
  #undef cb
  }
  
  void ArgminForwardImpl::exec(
          _megdnn_tensor_in src, _megdnn_tensor_out dst, _megdnn_workspace workspace) {
      check_exec(src.layout, dst.layout, workspace.size);
  #define cb(DType)                                                           \
      if (src.layout.dtype.enumv() == DTypeTrait<DType>::enumv) {             \
          using ctype = typename DTypeTrait<DType>::ctype;                    \
          MEGDNN_DISPATCH_CPU_KERN(                                           \
                  static_cast<HandleImpl*>(handle()),                         \
                  exec_forward<ctype MEGDNN_COMMA false>(src, dst, param())); \
      }
      MEGDNN_FOREACH_COMPUTING_DTYPE(cb)
  #undef cb
  }
  
  }  // namespace naive
  }  // namespace megdnn
  
  // vim: syntax=cpp.doxygen
  