/* Copyright (c) 2016 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. */

#pragma once

#include <fstream>
#include <string>
#include <vector>

#include "paddle/fluid/framework/data_type_transform.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/profiler.h"

namespace paddle {
namespace operators {
template <typename DeviceContext, typename T>
class LoadOpKernel : public framework::OpKernel<T> {
 public:
  void Compute(const framework::ExecutionContext &ctx) const override {
    auto place = ctx.GetPlace();
    // FIXME(yuyang18): We save variable to local file now, but we should change
    // it to save an output stream.
    auto filename = ctx.Attr<std::string>("file_path");
    std::ifstream fin(filename, std::ios::binary);
    PADDLE_ENFORCE(static_cast<bool>(fin), "Cannot open file %s for load op",
                   filename);

    auto out_var_name = ctx.OutputNames("Out").data();
    auto *out_var = ctx.OutputVar("Out");

    PADDLE_ENFORCE(out_var != nullptr, "Output variable %s cannot be found ",
                   out_var_name);

    PADDLE_ENFORCE(out_var != nullptr, "Output variable cannot be found ");

    if (out_var->IsType<framework::LoDTensor>()) {
      LoadLodTensor(fin, place, out_var, ctx);
    } else if (out_var->IsType<framework::SelectedRows>()) {
      LoadSelectedRows(fin, place, out_var);
    } else {
      PADDLE_ENFORCE(
          false,
          "Load only support LoDTensor and SelectedRows, %s has wrong type",
          out_var_name);
    }
  }

  void LoadLodTensor(std::istream &fin, const platform::Place &place,
                     framework::Variable *var,
                     const framework::ExecutionContext &ctx) const {
    // get device context from pool
    platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
    auto &dev_ctx = *pool.Get(place);
    auto *tensor = var->GetMutable<framework::LoDTensor>();

    auto seek = ctx.Attr<int64_t>("seek");

    if (seek != -1) {
      PADDLE_ENFORCE_GE(seek, 0,
                        platform::errors::InvalidArgument(
                            "seek witn tensor must great than or equal to 0"));
      auto shape = ctx.Attr<std::vector<int64_t>>("shape");
      DeserializeFromStream(fin, tensor, dev_ctx, seek, shape);
    } else {
      DeserializeFromStream(fin, tensor, dev_ctx);
    }

    auto load_as_fp16 = ctx.Attr<bool>("load_as_fp16");
    auto in_dtype = tensor->type();
    auto out_dtype = load_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;

    if (in_dtype != out_dtype) {
      // convert to float16 tensor
      auto in_kernel_type = framework::OpKernelType(in_dtype, place);
      auto out_kernel_type = framework::OpKernelType(out_dtype, place);
      framework::LoDTensor fp16_tensor;
      // copy LoD info to the new tensor
      fp16_tensor.set_lod(tensor->lod());
      framework::TransDataType(in_kernel_type, out_kernel_type, *tensor,
                               &fp16_tensor);

      // reset output tensor
      var->Clear();
      tensor = var->GetMutable<framework::LoDTensor>();
      tensor->set_lod(fp16_tensor.lod());
      tensor->ShareDataWith(fp16_tensor);
    }
  }

  void LoadSelectedRows(std::istream &fin, const platform::Place &place,
                        framework::Variable *var) const {
    auto *selectedRows = var->GetMutable<framework::SelectedRows>();
    // get device context from pool
    platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
    auto &dev_ctx = *pool.Get(place);
    framework::DeserializeFromStream(fin, selectedRows, dev_ctx);
    selectedRows->SyncIndex();
  }
};

}  // namespace operators
}  // namespace paddle
