/* 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 <memory>
#include <numeric>

#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 {

// 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::OperatorBase {
 public:
  SaveOp(const std::string &type, const framework::VariableNameMap &inputs,
         const framework::VariableNameMap &outputs,
         const framework::AttributeMap &attrs)
      : OperatorBase(type, inputs, outputs, attrs) {}

 private:
  void RunImpl(const framework::Scope &scope,
               const platform::Place &place) const override {
    auto iname = Input("X");
    auto *var = scope.FindVar(iname);
    PADDLE_ENFORCE(var != nullptr, "Cannot find variable %s for save_op",
                   iname);

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

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

    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::unique_ptr<std::ofstream> fout;
    if (format == "windows") {
      fout.reset(new std::ofstream(filename,
                                   std::ios_base::out | std::ios_base::binary));
    } else {
      fout.reset(new std::ofstream(filename));
    }
    PADDLE_ENFORCE(static_cast<bool>(*fout), "Cannot open %s to write",
                   filename);

    auto save_as_fp16 = Attr<bool>("save_as_fp16");
    auto in_dtype = framework::ToDataType(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);
    }
  }

  void SaveSelectedRows(const framework::Scope &scope,
                        const platform::Place &place,
                        framework::Variable *var) const {
    auto *lt_var = scope.FindVar(LOOKUP_TABLE_PATH)->GetMutable<std::string>();
    PADDLE_ENFORCE(
        lt_var != nullptr,
        "Can not find variable kLookupTablePath for SaveSelectedRows");
    std::string filename = lt_var->data();
    auto format = Attr<std::string>("format");
    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::unique_ptr<std::ofstream> fout;
    if (format == "windows") {
      fout.reset(new std::ofstream(filename,
                                   std::ios_base::out | std::ios_base::binary));
    } else {
      fout.reset(new std::ofstream(filename));
    }
    PADDLE_ENFORCE(static_cast<bool>(*fout), "Cannot open %s to write",
                   filename);
    framework::SerializeToStream(*fout, selectedRows, dev_ctx);
  }
};

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(); });
    AddAttr<std::string>("format",
                         R"DOC((windows|linux)" "saved model file format
                         windows and linux file newline symbol is
different. windows(newline is \n\r) or linux(newline is \r)
So if you set attribute format to windows, then we saved model file in binary.
It can be used both linux and windows. If you set format to linux,
it will save file in normal file, newline symbol is \r. Need to note
that these two format is not inter-compatible.)DOC")
        .SetDefault("linux")
        .AddCustomChecker([](const std::string &s) {
          return s == "windows" || s == "linux";
        });
  }
};

class SaveOpVarTypeInference : public framework::VarTypeInference {
 public:
  void operator()(const framework::OpDesc &op_desc,
                  framework::BlockDesc *block) const override {
    auto out_var_name = op_desc.Output(LOOKUP_TABLE_PATH).front();
    auto &out_var = block->FindRecursiveOrCreateVar(out_var_name);
    auto var_type = framework::proto::VarType::RAW;
    out_var.SetType(var_type);
  }
};

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

namespace ops = paddle::operators;

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