// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#include "lite/kernels/arm/conv_winograd.h"
#include <vector>
#include "lite/backends/arm/math/conv_impl.h"
#include "lite/backends/arm/math/packed_sgemm.h"

namespace paddle {
namespace lite {
namespace kernels {
namespace arm {

template <>
void WinogradConv<PRECISION(kFloat), PRECISION(kFloat)>::ReInitWhenNeeded() {
  auto& param = this->Param<param_t>();
  auto& ctx = this->ctx_->template As<ARMContext>();

  auto x_dims = param.x->dims();
  auto w_dims = param.filter->dims();
  auto o_dims = param.output->dims();

  if (last_shape_ == x_dims) {
    return;
  }

  int ic = x_dims[1];
  int ow = o_dims[3];
  int oh = o_dims[2];
  int oc = o_dims[1];
  int tile_w = (ow + 5) / 6;
  int tile_h = (oh + 5) / 6;
  int size_tile = tile_h * tile_w;
  int size_trans_channel = 8 * 8 * size_tile;
  int max_ch = ic > oc ? ic : oc;

  const int n_wino = size_tile;
  workspace_size_ = (size_trans_channel * max_ch * 2 + n_wino) * sizeof(float);
  last_shape_ = x_dims;
}

template <>
void WinogradConv<PRECISION(kFloat), PRECISION(kFloat)>::PrepareForRun() {
  auto& param = this->Param<param_t>();
  auto& ctx = this->ctx_->template As<ARMContext>();

  auto x_dims = param.x->dims();
  auto w_dims = param.filter->dims();
  auto o_dims = param.output->dims();
  last_shape_ = x_dims;

  int ic = x_dims[1];
  int ow = o_dims[3];
  int oh = o_dims[2];
  int oc = o_dims[1];
  int tile_w = (ow + 5) / 6;
  int tile_h = (oh + 5) / 6;
  int size_tile = tile_h * tile_w;
  int size_trans_channel = 8 * 8 * size_tile;
  int max_ch = ic > oc ? ic : oc;

  const int m_wino = oc;
  const int n_wino = size_tile;
  int hblock = lite::arm::math::get_hblock(&ctx);
  int m_round = hblock * ((m_wino + hblock - 1) / hblock);
  weights_.Resize({1, 1, 1, 8 * 8 * m_round * ic});
  workspace_size_ = (size_trans_channel * max_ch * 2 + n_wino) * sizeof(float);
  auto weights_wino =
      static_cast<float*>(malloc(sizeof(float) * 8 * 8 * oc * ic));
  void* trans_tmp_ptr = malloc(sizeof(float) * 8 * 8 * oc * ic);
  lite::arm::math::winograd_transform_weights(
      weights_wino, param.filter->data<float>(), oc, ic, trans_tmp_ptr);
  auto weights_trans = weights_.mutable_data<float>();
  for (int i = 0; i < 64; ++i) {
    float* packed_weights = weights_trans + i * m_round * ic;
    const float* weights_wino_ptr = weights_wino + i * oc * ic;
    lite::arm::math::prepackA(packed_weights,
                              weights_wino_ptr,
                              1.f,
                              ic,
                              0,
                              m_wino,
                              0,
                              ic,
                              false,
                              &ctx);
  }
  free(trans_tmp_ptr);
  free(weights_wino);
}

template <>
void WinogradConv<PRECISION(kFloat), PRECISION(kFloat)>::Run() {
  auto& param = this->Param<param_t>();
  auto& ctx = this->ctx_->template As<ARMContext>();
  // extend workspace
  ctx.ExtendWorkspace(workspace_size_);

  const auto* i_data = param.x->data<float>();
  const auto* w_data = weights_.data<float>();
  const auto* b_data = param.bias ? param.bias->data<float>() : nullptr;
  auto* o_data = param.output->mutable_data<float>();

  auto x_dims = param.x->dims();
  auto w_dims = param.filter->dims();
  auto o_dims = param.output->dims();

  int iw = x_dims[3];  // nchw
  int ih = x_dims[2];
  int ic = x_dims[1];
  int bs = x_dims[0];
  int oh = o_dims[2];
  int ow = o_dims[3];
  int oc = o_dims[1];

  lite::arm::math::conv_winograd3x3(
      i_data, o_data, bs, oc, oh, ow, ic, ih, iw, w_data, b_data, param, &ctx);
}

}  // namespace arm
}  // namespace kernels
}  // namespace lite
}  // namespace paddle