text: /**
   * \file dnn/src/arm_common/conv_bias/fp32/algos.h
   * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
   *
   * Copyright (c) 2014-2020 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.
   */
  
  #pragma once
  
  #include "src/arm_common/conv_bias/opr_impl.h"
  #include "src/fallback/matrix_mul/opr_impl.h"
  
  namespace megdnn {
  namespace arm_common {
  class ConvBiasImpl::AlgoFP32WinogradF23_4x4 final : public AlgoBase {
  public:
      AlgoFP32WinogradF23_4x4(fallback::MatrixMulImpl::AlgoBase* matmul_algo,
                              uint32_t tile_size)
              : m_matmul_algo{matmul_algo}, m_tile_size{tile_size} {}
      const char* name() const override {
          if (m_name.empty()) {
              m_name = ConvBiasImpl::algo_name<ConvBias::WinogradParam>(
                      m_matmul_algo->name(), {4, 2, m_tile_size});
          }
          return m_name.c_str();
      }
      MEGDNN_WINOGRAD_ALGO_FUN_DECLARE();
  };
  
  class ConvBiasImpl::AlgoFP32WinogradF63 final : public AlgoBase {
  public:
      AlgoFP32WinogradF63(fallback::MatrixMulImpl::AlgoBase* matmul_algo,
                          uint32_t tile_size)
              : m_matmul_algo{matmul_algo}, m_tile_size{tile_size} {}
      const char* name() const override {
          if (m_name.empty()) {
              m_name = ConvBiasImpl::algo_name<ConvBias::WinogradParam>(
                      m_matmul_algo->name(), {1, 6, m_tile_size});
          }
          return m_name.c_str();
      }
      MEGDNN_WINOGRAD_ALGO_FUN_DECLARE();
  };
  
  class ConvBiasImpl::AlgoFP32WinogradF63_4x4 final : public AlgoBase {
  public:
      AlgoFP32WinogradF63_4x4(fallback::MatrixMulImpl::AlgoBase* matmul_algo,
                              uint32_t tile_size)
              : m_matmul_algo{matmul_algo}, m_tile_size{tile_size} {}
      const char* name() const override {
          if (m_name.empty()) {
              m_name = ConvBiasImpl::algo_name<ConvBias::WinogradParam>(
                      m_matmul_algo->name(), {4, 6, m_tile_size});
          }
          return m_name.c_str();
      }
      MEGDNN_WINOGRAD_ALGO_FUN_DECLARE();
  };
  
  class ConvBiasImpl::AlgoFP32WinogradF54 final : public AlgoBase {
  public:
      AlgoFP32WinogradF54(fallback::MatrixMulImpl::AlgoBase* matmul_algo,
                          uint32_t tile_size)
              : m_matmul_algo{matmul_algo}, m_tile_size{tile_size} {}
      const char* name() const override {
          if (m_name.empty()) {
              m_name = ConvBiasImpl::algo_name<ConvBias::WinogradParam>(
                      m_matmul_algo->name(), {1, 5, m_tile_size});
          }
          return m_name.c_str();
      }
      MEGDNN_WINOGRAD_ALGO_FUN_DECLARE();
  };
  
  class ConvBiasImpl::AlgoFP32WinogradF45 final : public AlgoBase {
  public:
      AlgoFP32WinogradF45(fallback::MatrixMulImpl::AlgoBase* matmul_algo,
                          uint32_t tile_size)
              : m_matmul_algo{matmul_algo}, m_tile_size{tile_size} {}
      const char* name() const override {
          if (m_name.empty()) {
              m_name = ConvBiasImpl::algo_name<ConvBias::WinogradParam>(
                      m_matmul_algo->name(), {1, 4, m_tile_size});
          }
          return m_name.c_str();
      }
      MEGDNN_WINOGRAD_ALGO_FUN_DECLARE();
  };
  
  //===================== NCHW44 Winograd Support =====================//
  class ConvBiasImpl::AlgoFP32WinogradF23_4x4_NCHW44 final : public AlgoBase {
  public:
      AlgoFP32WinogradF23_4x4_NCHW44(
              fallback::MatrixMulImpl::AlgoBase* matmul_algo, uint32_t tile_size)
              : m_matmul_algo{matmul_algo}, m_tile_size{tile_size} {}
      const char* name() const override {
          if (m_name.empty()) {
              m_name = ConvBiasImpl::algo_name<ConvBias::WinogradParam>(
                      m_matmul_algo->name(), {4, 2, m_tile_size},
                      param::ConvBias::Format::NCHW44);
          }
          return m_name.c_str();
      }
      MEGDNN_WINOGRAD_ALGO_FUN_DECLARE();
  };
  
  class ConvBiasImpl::AlgoFP32WinogradF63_4x4_NCHW44 final : public AlgoBase {
  public:
      AlgoFP32WinogradF63_4x4_NCHW44(
              fallback::MatrixMulImpl::AlgoBase* matmul_algo, uint32_t tile_size)
              : m_matmul_algo{matmul_algo}, m_tile_size{tile_size} {}
      const char* name() const override {
          if (m_name.empty()) {
              m_name = ConvBiasImpl::algo_name<ConvBias::WinogradParam>(
                      m_matmul_algo->name(), {4, 6, m_tile_size},
                      param::ConvBias::Format::NCHW44);
          }
          return m_name.c_str();
      }
      MEGDNN_WINOGRAD_ALGO_FUN_DECLARE();
  };
  // ================================================================= //
  
  class ConvBiasImpl::AlgoF32Direct final : public AlgoBase {
      SmallVector<NCBKern> get_kimpls(const NCBKernSizeParam& param) const;
      bool m_large_group;
  
  public:
      AlgoF32Direct(bool is_large_group) : m_large_group{is_large_group} {}
      bool is_reproducible() const override { return true; }
      const char* name() const override {
          return m_large_group ? "F32DIRECT_LARGE_GROUP"
                               : "F32DIRECT_SMALL_GROUP";
      }
      bool usable(fallback::ConvBiasImpl* opr, const NCBKernSizeParam& param,
                  AlgoSelectionStrategy algo_selection_strategy) const override;
  
      size_t get_workspace(fallback::ConvBiasImpl* opr,
                           const NCBKernSizeParam& param) const override;
      virtual SmallVector<NCBKern> dispatch_kerns(
              fallback::ConvBiasImpl* opr,
              const NCBKernSizeParam& param) const override;
  };
  
  class ConvBiasImpl::AlgoF32DirectStride1 final : public AlgoBase {
      SmallVector<NCBKern> get_kimpls(const NCBKernSizeParam& param) const;
      bool m_large_group;
  
  public:
      AlgoF32DirectStride1(bool is_large_group) : m_large_group{is_large_group} {}
      bool is_reproducible() const override { return true; }
      const char* name() const override {
          return m_large_group ? "F32STRD1_LARGE_GROUP" : "F32STRD1_SMALL_GROUP";
      }
      bool usable(fallback::ConvBiasImpl*, const NCBKernSizeParam& param,
                  AlgoSelectionStrategy algo_selection_strategy) const override;
  
      size_t get_workspace(fallback::ConvBiasImpl*,
                           const NCBKernSizeParam& param) const override;
      virtual SmallVector<NCBKern> dispatch_kerns(
              fallback::ConvBiasImpl* opr,
              const NCBKernSizeParam& param) const override;
  };
  
  class ConvBiasImpl::AlgoF32DirectStride2 final : public AlgoBase {
      SmallVector<NCBKern> get_kimpls(const NCBKernSizeParam& param) const;
      bool m_large_group;
  
  public:
      AlgoF32DirectStride2(bool is_large_group) : m_large_group{is_large_group} {}
      bool is_reproducible() const override { return true; }
      const char* name() const override {
          return m_large_group ? "F32STRD2_LARGE_GROUP" : "F32STRD2_SMALL_GROUP";
      }
      bool usable(fallback::ConvBiasImpl*, const NCBKernSizeParam& param,
                  AlgoSelectionStrategy algo_selection_strategy) const override;
  
      size_t get_workspace(fallback::ConvBiasImpl*,
                           const NCBKernSizeParam& param) const override;
      virtual SmallVector<NCBKern> dispatch_kerns(
              fallback::ConvBiasImpl* opr,
              const NCBKernSizeParam& param) const override;
  };
  
  class ConvBiasImpl::AlgoF32DirectNCHW44 final : public AlgoBase {
      SmallVector<NCBKern> get_kimpls(const NCBKernSizeParam& param) const;
  
  public:
      AlgoF32DirectNCHW44() {}
      bool is_reproducible() const override { return true; }
      const char* name() const override { return "F32_CONV_NCHW44_DIRECT"; }
      bool usable(fallback::ConvBiasImpl*, const NCBKernSizeParam& param,
                  AlgoSelectionStrategy algo_selection_strategy) const override;
  
      size_t get_workspace(fallback::ConvBiasImpl*,
                           const NCBKernSizeParam& param) const override;
      virtual SmallVector<NCBKern> dispatch_kerns(
              fallback::ConvBiasImpl* opr,
              const NCBKernSizeParam& param) const override;
  };
  
  class ConvBiasImpl::AlgoF32DirectNCHWNCHW44 final : public AlgoBase {
      SmallVector<NCBKern> get_kimpls(const NCBKernSizeParam& param) const;
  
  public:
      AlgoF32DirectNCHWNCHW44() {}
      bool is_reproducible() const override { return true; }
      const char* name() const override { return "F32_CONV_NCHW_NCHW44"; }
      bool usable(fallback::ConvBiasImpl* opr, const NCBKernSizeParam& param,
                  AlgoSelectionStrategy algo_selection_strategy) const override;
  
      size_t get_workspace(fallback::ConvBiasImpl* opr,
                           const NCBKernSizeParam& param) const override;
      virtual SmallVector<NCBKern> dispatch_kerns(
              fallback::ConvBiasImpl* opr,
              const NCBKernSizeParam& param) const override;
  };
  
  class ConvBiasImpl::AlgoF32ChannelWiseNCHW44 final : public AlgoBase {
      SmallVector<NCBKern> get_kimpls(const NCBKernSizeParam& param) const;
  
  public:
      bool is_reproducible() const override { return true; }
      const char* name() const override { return "F32_CHANNEL_WISE_NCHW44"; }
      bool usable(fallback::ConvBiasImpl* opr, const NCBKernSizeParam& param,
                  AlgoSelectionStrategy algo_selection_strategy) const override;
  
      size_t get_workspace(fallback::ConvBiasImpl* opr,
                           const NCBKernSizeParam& param) const override;
      virtual SmallVector<NCBKern> dispatch_kerns(
              fallback::ConvBiasImpl* opr,
              const NCBKernSizeParam& param) const override;
  };
  
  }  // namespace arm_common
  }  // namespace megdnn
  
  #undef MEGDNN_WINOGRAD_ALGO_FUN_DECLARE
  
  // vim: syntax=cpp.doxygen
  