/* 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 <fstream>
#include "paddle/fluid/framework/data_type_transform.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/device_context.h"

namespace paddle {
namespace operators {

class LoadCombineOp : public framework::OperatorBase {
 public:
  LoadCombineOp(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 filename = Attr<std::string>("file_path");
    auto load_as_fp16 = Attr<bool>("load_as_fp16");
    auto model_from_memory = Attr<bool>("model_from_memory");
    auto out_var_names = Outputs("Out");
    PADDLE_ENFORCE_GT(
        static_cast<int>(out_var_names.size()), 0,
        "The number of output variables should be greater than 0.");
    if (!model_from_memory) {
      std::ifstream fin(filename);
      PADDLE_ENFORCE(static_cast<bool>(fin),
                     "Cannot open file %s for load_combine op", filename);
      LoadParamsFromBuffer(scope, place, &fin, load_as_fp16, out_var_names);
    } else {
      PADDLE_ENFORCE(!filename.empty(), "Cannot load file from memory");
      std::stringstream fin(filename);
      LoadParamsFromBuffer(scope, place, &fin, load_as_fp16, out_var_names);
    }
  }
  void LoadParamsFromBuffer(
      const framework::Scope &scope, const platform::Place &place,
      std::istream *buffer, bool load_as_fp16,
      const std::vector<std::string> &out_var_names) const {
    platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
    auto &dev_ctx = *pool.Get(place);

    for (size_t i = 0; i < out_var_names.size(); i++) {
      auto *out_var = scope.FindVar(out_var_names[i]);

      PADDLE_ENFORCE(out_var != nullptr, "Output variable %s cannot be found",
                     out_var_names[i]);

      auto *tensor = out_var->GetMutable<framework::LoDTensor>();

      // Error checking
      PADDLE_ENFORCE(static_cast<bool>(buffer), "Cannot read more");

      // Get data from fin to tensor
      DeserializeFromStream(*buffer, tensor, dev_ctx);

      auto in_dtype = framework::ToDataType(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
        out_var->Clear();
        tensor = out_var->GetMutable<framework::LoDTensor>();
        tensor->set_lod(fp16_tensor.lod());
        tensor->ShareDataWith(fp16_tensor);
      }
    }
  }
};

class LoadCombineOpProtoMaker : public framework::OpProtoAndCheckerMaker {
 public:
  void Make() override {
    AddOutput(
        "Out",
        "(vector) The output LoDTensors that will be read from the input file.")
        .AsDuplicable();
    AddAttr<bool>(
        "load_as_fp16",
        "(boolean, default false)"
        "If true, the tensor will be first loaded and then "
        "converted to float16 data type. Otherwise, the tensor will be "
        "directly loaded without data type conversion.")
        .SetDefault(false);
    AddAttr<std::string>("file_path",
                         "(string) "
                         "LoDTensors will be loaded from \"file_path\".")
        .AddCustomChecker(
            [](const std::string &path) { return !path.empty(); });
    AddAttr<bool>("model_from_memory",
                  "(boolean, default false)"
                  "If true, file_path is in memory, and LoDTensors will be "
                  "loaded directly from memory")
        .SetDefault(false);
    AddComment(R"DOC(
LoadCombine Operator.

LoadCombine operator loads LoDTensor variables from a file, which could be 
loaded in memory already. The file should contain one or more LoDTensors 
serialized using the SaveCombine operator. The
LoadCombine operator applies a deserialization strategy to appropriately load 
the LodTensors, and this strategy complements the serialization strategy used 
in the SaveCombine operator. Hence, the LoadCombine operator is tightly coupled
with the SaveCombine operator, and can only deserialize one or more LoDTensors 
that were saved using the SaveCombine operator.

)DOC");
  }
};
}  // namespace operators
}  // namespace paddle
namespace ops = paddle::operators;

REGISTER_OPERATOR(load_combine, ops::LoadCombineOp,
                  ops::LoadCombineOpProtoMaker);