/* Copyright (c) 2018 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 "io/loader.h"

#include "framework/lod_tensor.h"
#include "framework/program/program-optimize/program_optimize.h"

namespace paddle_mobile {
using framework::Variable;

static size_t ReadBuffer(const char *file_name, uint8_t **out) {
  FILE *fp;
  fp = fopen(file_name, "rb");
  PADDLE_MOBILE_ENFORCE(fp != NULL, " %s open failed !", file_name);

  fseek(fp, 0, SEEK_END);
  size_t size = ftell(fp);
  rewind(fp);

  DLOG << "model size: " << size;

  *out = reinterpret_cast<uint8_t *>(malloc(size));

  size_t cur_len = 0;
  size_t nread;
  while ((nread = fread(*out + cur_len, 1, size - cur_len, fp)) != 0) {
    cur_len += nread;
  }
  fclose(fp);
  return cur_len;
}

template <typename Dtype, Precision P>
const framework::Program<Dtype, P> Loader<Dtype, P>::Load(
    const std::string &dirname, bool optimize, bool quantification,
    bool can_add_split) {
  auto program = this->LoadProgram(dirname + "/__model__", optimize,
                                   quantification, can_add_split);
  program.model_path = dirname;
  return program;
}

template <typename Dtype, Precision P>
const framework::Program<Dtype, P> Loader<Dtype, P>::Load(
    const std::string &model_path, const std::string &para_path, bool optimize,
    bool quantification) {
  auto program = this->LoadProgram(model_path, optimize, quantification);

  program.para_path = para_path;
  program.combined = true;
  program.quantification = quantification;
  return program;
}

template <typename Dtype, Precision P>
const framework::Program<Dtype, P> Loader<Dtype, P>::LoadProgram(
    const std::string &model_path, bool optimize, bool quantification,
    bool can_add_split) {
  std::string model_filename = model_path;
  PaddleMobile__Framework__Proto__ProgramDesc *c_program;
  uint8_t *buf = NULL;
  size_t read_size = ReadBuffer(model_filename.c_str(), &buf);

  PADDLE_MOBILE_ENFORCE(buf != NULL, "read from __model__ is null");

  c_program = paddle_mobile__framework__proto__program_desc__unpack(
      NULL, read_size, buf);
  //
  PADDLE_MOBILE_ENFORCE(c_program != NULL, "program is null");
  //
  DLOG << "n_ops: " << (*c_program->blocks)->n_ops;
  //
  auto originProgramDesc = std::make_shared<framework::ProgramDesc>(c_program);

  framework::Program<Dtype, P> program;
  program.originProgram = originProgramDesc;
  program.quantification = quantification;

  auto scope = std::make_shared<framework::Scope>();
  program.scope = scope;

  for (const auto &block : originProgramDesc->Blocks()) {
    for (auto var_desc : block->Vars()) {
      auto var = scope->Var(var_desc->Name());

      if (var_desc->Type() == framework::VARTYPE_TYPE_LOD_TENSOR) {
        if (var_desc->Persistable() &&
            var_desc->Type() != framework::VARTYPE_TYPE_FEED_MINIBATCH &&
            var_desc->Type() != framework::VARTYPE_TYPE_FETCH_LIST) {
          auto dim = var_desc->Tensor_desc().Dims();
          auto tensor = var->GetMutable<framework::LoDTensor>();
          tensor->Resize(framework::make_ddim(dim));
        } else {
          auto dim = var_desc->Tensor_desc().Dims();
          PADDLE_MOBILE_ENFORCE(dim.size() > 0, "dim size is 0");
          dim[0] = 1;
          auto tensor = var->GetMutable<framework::LoDTensor>();
          tensor->Resize(framework::make_ddim(dim));
        }
      } else {
        // TODO(codeWorm): some.
      }
    }
  }

  if (optimize) {
    framework::ProgramOptimize program_optimize;
    program.optimizeProgram =
        program_optimize.FusionOptimize(originProgramDesc, can_add_split);
  }
  if (optimize) {
    program.optimizeProgram->Description("optimize: ");
  } else {
    originProgramDesc->Description("program: ");
  }

  paddle_mobile__framework__proto__program_desc__free_unpacked(c_program, NULL);
  return program;
}

template class Loader<CPU, Precision::FP32>;
template class Loader<FPGA, Precision::FP32>;
template class Loader<GPU_MALI, Precision::FP32>;

}  // namespace paddle_mobile