/* 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. */

#include <stdint.h>
#include <fstream>
#include <numeric>
#include <vector>

#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/framework/data_type_transform.h"
#include "paddle/fluid/framework/framework.pb.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/framework/variable.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/port.h"

namespace paddle {
namespace operators {

using Tensor = framework::Tensor;
using LoDTensor = framework::LoDTensor;

// define LOOKUP_TABLE_PATH for checkpoint notify to save lookup table variables
// to directory specified.
constexpr char LOOKUP_TABLE_PATH[] = "kLookupTablePath";

class SaveOp : public framework::OperatorWithKernel {
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;

  void InferShape(framework::InferShapeContext *ctx) const override {}

 protected:
  framework::OpKernelType GetExpectedKernelType(
      const framework::ExecutionContext &ctx) const override {
    return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
                                   ctx.GetPlace());
  }
};

class SaveOpProtoMaker : public framework::OpProtoAndCheckerMaker {
 public:
  void Make() override {
    AddInput("X", "(Tensor ) Input LoDTensor and SelectedRows to be saved");
    AddComment(R"DOC(
Save operator

This operator will serialize and write LoDTensor / SelectedRows variable to file on disk.
)DOC");
    AddAttr<bool>("overwrite",
                  "(boolean, default true)"
                  "Overwrite the output file if exist")
        .SetDefault(true);
    AddAttr<bool>("save_as_fp16",
                  "(boolean, default false)"
                  "If true, the tensor will be converted to float16 data "
                  "type and then saved. Otherwise, the tensor will be "
                  "directly saved without data type conversion.")
        .SetDefault(false);
    AddAttr<std::string>("file_path",
                         "(string)"
                         "The \"file_path\" where the variable will be saved.")
        .AddCustomChecker(
            [](const std::string &path) { return !path.empty(); });
    AddOutput(LOOKUP_TABLE_PATH,
              "(string)"
              "for pserver: The \"kLookupTablePath\" where checkpoint notify "
              "to save lookup table variables"
              " to directory specified.")
        .AsDispensable();
  }
};

class SaveOpVarTypeInference : public framework::VarTypeInference {
 public:
  void operator()(framework::InferVarTypeContext *ctx) const override {
    auto var_type = framework::proto::VarType::RAW;
    ctx->SetType(LOOKUP_TABLE_PATH, var_type);
  }
};

class SaveOpShapeInference : public framework::InferShapeBase {
 public:
  void operator()(framework::InferShapeContext *ctx) const override {}
};

template <typename DeviceContext, typename T>
class SaveOpKernel : public framework::OpKernel<T> {
 public:
  void Compute(const framework::ExecutionContext &ctx) const override {
    auto place = ctx.GetPlace();

    auto *input_var = ctx.InputVar("X");
    auto iname = ctx.Inputs("X").data();
    PADDLE_ENFORCE(input_var != nullptr, "Cannot find variable %s for save_op",
                   iname);

    if (input_var->IsType<framework::LoDTensor>()) {
      SaveLodTensor(ctx, place, input_var);
    } else if (input_var->IsType<framework::SelectedRows>()) {
      SaveSelectedRows(ctx, place, input_var);
    } else {
      PADDLE_ENFORCE(
          false,
          "SaveOp only support LoDTensor and SelectedRows, %s has wrong type",
          iname);
    }
  }

  void SaveLodTensor(const framework::ExecutionContext &ctx,
                     const platform::Place &place,
                     const framework::Variable *var) const {
    auto filename = ctx.Attr<std::string>("file_path");
    auto overwrite = ctx.Attr<bool>("overwrite");

    if (FileExists(filename) && !overwrite) {
      PADDLE_THROW("%s is existed, cannot save to it when overwrite=false",
                   filename, overwrite);
    }

    MkDirRecursively(DirName(filename).c_str());

    auto &tensor = var->Get<framework::LoDTensor>();

    // get device context from pool
    platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
    auto &dev_ctx = *pool.Get(place);

    // FIXME(yuyang18): We save variable to local file now, but we should change
    // it to save an output stream.
    std::ofstream fout(filename, std::ios::binary);
    PADDLE_ENFORCE(static_cast<bool>(fout), "Cannot open %s to write",
                   filename);

    auto save_as_fp16 = ctx.Attr<bool>("save_as_fp16");
    auto in_dtype = tensor.type();
    auto out_dtype = save_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;

    if (in_dtype != out_dtype) {
      auto in_kernel_type = framework::OpKernelType(in_dtype, place);
      auto out_kernel_type = framework::OpKernelType(out_dtype, place);
      framework::LoDTensor out;
      framework::TransDataType(in_kernel_type, out_kernel_type, tensor, &out);
      // copy LoD info to the new tensor
      out.set_lod(tensor.lod());
      framework::SerializeToStream(fout, out, dev_ctx);
    } else {
      framework::SerializeToStream(fout, tensor, dev_ctx);
    }
    fout.close();
  }

  void SaveSelectedRows(const framework::ExecutionContext &ctx,
                        const platform::Place &place,
                        const framework::Variable *var) const {
    framework::Variable *out_put_var = ctx.OutputVar(LOOKUP_TABLE_PATH);
    PADDLE_ENFORCE(
        out_put_var != nullptr,
        "Can not find variable kLookupTablePath for SaveSelectedRows");
    auto *lt_var = out_put_var->GetMutable<std::string>();

    std::string filename = lt_var->data();
    VLOG(4) << "SaveSelectedRows get File name: " << filename;

    MkDirRecursively(DirName(filename).c_str());

    auto &selectedRows = var->Get<framework::SelectedRows>();

    // get device context from pool
    platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
    auto &dev_ctx = *pool.Get(place);

    // FIXME(yuyang18): We save variable to local file now, but we should change
    // it to save an output stream.
    std::ofstream fout(filename, std::ios::binary);
    PADDLE_ENFORCE(static_cast<bool>(fout), "Cannot open %s to write",
                   filename);
    framework::SerializeToStream(fout, selectedRows, dev_ctx);
    fout.close();
  }
};

}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;

REGISTER_OPERATOR(save, ops::SaveOp, ops::SaveOpProtoMaker,
                  ops::SaveOpVarTypeInference, ops::SaveOpShapeInference);

REGISTER_OP_CPU_KERNEL(
    save, ops::SaveOpKernel<paddle::platform::CPUDeviceContext, float>,
    ops::SaveOpKernel<paddle::platform::CPUDeviceContext, double>,
    ops::SaveOpKernel<paddle::platform::CPUDeviceContext, int>,
    ops::SaveOpKernel<paddle::platform::CPUDeviceContext, int8_t>,
    ops::SaveOpKernel<paddle::platform::CPUDeviceContext, int64_t>);