// 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 "paddle/fluid/framework/convert_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/reader.h"
#include "paddle/fluid/platform/profiler/event_tracing.h"

namespace paddle {
namespace operators {

// Returns true if the two dimensions are compatible.
// A dimension is compatible with the other if:
// 1. The length of the dimensions are same.
// 2. Each non-negative number of the two dimensions are same.
// 3. For negative number in a dimension, it means unknown so it is compatible
//    with any number.
bool DimensionIsCompatibleWith(const framework::DDim& first,
                               const framework::DDim& second) {
  int dim_size = first.size();
  if (dim_size != second.size()) {
    return false;
  }
  for (int i = 0; i < dim_size; ++i) {
    if (first[i] >= 0 && second[i] >= 0 && first[i] != second[i]) {
      return false;
    }
  }
  return true;
}

class ReadInferShape : public framework::InferShapeBase {
 public:
  void operator()(framework::InferShapeContext* ctx) const override {
    OP_INOUT_CHECK(ctx->HasInput("Reader"), "Input", "Reader", "read");
    OP_INOUT_CHECK(ctx->HasOutputs("Out"), "Output", "Out", "read");
    if (!ctx->IsRuntime() && ctx->Attrs().Get<bool>("infer_out")) {
      std::vector<framework::DDim> reader_dims = ctx->GetReaderDims("Reader");
      std::vector<std::string> out_names = ctx->Outputs("Out");
      PADDLE_ENFORCE_EQ(
          reader_dims.size(),
          out_names.size(),
          platform::errors::InvalidArgument(
              "The reader's dim number doesn't match the output number."));
      ctx->SetOutputsDim("Out", reader_dims);
      auto in_desc =
          PADDLE_GET(framework::VarDesc*, ctx->GetInputVarPtrs("Reader")[0]);
      auto in_lod_levels = in_desc->GetLoDLevels();
      auto out_var_ptrs = ctx->GetOutputVarPtrs("Out");
      PADDLE_ENFORCE_EQ(
          in_lod_levels.size(),
          out_var_ptrs.size(),
          platform::errors::InvalidArgument(
              "LoDLevels of Input(Reader) must be the same as the "
              "number of Outputs(Out)."));
      for (size_t i = 0; i < out_var_ptrs.size(); ++i) {
        auto* out_desc = PADDLE_GET(framework::VarDesc*, out_var_ptrs[i]);
        out_desc->SetLoDLevel(in_lod_levels[i]);
      }
    }
  }
};

class ReadInferVarType : public framework::StaticGraphVarTypeInference {
 public:
  void operator()(framework::InferVarTypeContext* ctx) const override {
    bool infer_out = PADDLE_GET_CONST(bool, ctx->GetAttr("infer_out"));
    if (infer_out) {
      std::string reader_name = Input(ctx, "Reader")[0];
      auto& out_names = Output(ctx, "Out");
      auto dtypes = GetDataTypes(ctx, reader_name);
      PADDLE_ENFORCE_EQ(dtypes.size(),
                        out_names.size(),
                        platform::errors::InvalidArgument(
                            "The number of input reader's dtypes do not match "
                            "the output variable number."));
      for (size_t i = 0; i < dtypes.size(); ++i) {
        SetType(ctx, out_names[i], framework::proto::VarType::LOD_TENSOR);
        SetDataType(ctx, out_names[i], dtypes[i]);
      }
    }
  }
};

class ReadOp : public framework::OperatorBase {
 public:
  using framework::OperatorBase::OperatorBase;

 private:
  void RunImpl(const framework::Scope& scope,
               const platform::Place& dev_place) const override {
    VLOG(3) << "read op in";
    framework::ReaderHolder* reader =
        GET_DATA_SAFELY(
            scope.FindVar(Input("Reader")), "Input", "Reader", "Read")
            .GetMutable<framework::ReaderHolder>();
    std::vector<std::string> out_arg_names = Outputs("Out");
    paddle::framework::LoDTensorArray ins;

    // For profiling
    platform::RecordEvent record_event(
        Type().c_str(), platform::TracerEventType::UserDefined, 1);

    reader->ReadNext(&ins);
    if (ins.empty()) {
      VLOG(3) << "throw_eof_exp";
      PADDLE_THROW_EOF();
    }
    PADDLE_ENFORCE_EQ(
        ins.size(),
        out_arg_names.size(),
        platform::errors::InvalidArgument("input data number and output data "
                                          "number of read_op do not match"));

    const std::vector<framework::DDim>& shapes = reader->Shapes();
    const std::vector<framework::proto::VarType::Type>& var_types =
        reader->VarTypes();
    const std::vector<bool>& need_check_feed = reader->NeedCheckFeed();
    PADDLE_ENFORCE_EQ(
        out_arg_names.size(),
        need_check_feed.size(),
        platform::errors::InvalidArgument(
            "Output size of read_op and the number of fed "
            "variables of reader do not match. Received size of output is %d, "
            "number of fed variables of reader is %d",
            out_arg_names.size(),
            need_check_feed.size()));

    for (size_t i = 0; i < out_arg_names.size(); ++i) {
      auto* out =
          scope.FindVar(out_arg_names[i])->GetMutable<phi::DenseTensor>();
      if (need_check_feed[i]) {
        auto in_dims = ins[i].dims();
        PADDLE_ENFORCE_EQ(
            DimensionIsCompatibleWith(shapes[i], in_dims),
            true,
            platform::errors::InvalidArgument(
                "The fed Variable %s should have dimensions = %d, "
                "shape = [%s], but received fed shape [%s]",
                out_arg_names[i],
                shapes[i].size(),
                shapes[i],
                in_dims));
        PADDLE_ENFORCE_EQ(
            framework::TransToProtoVarType(ins[i].dtype()),
            var_types[i],
            platform::errors::InvalidArgument(
                "The data type of fed Variable %s must be %s, but received %s",
                out_arg_names[i],
                var_types[i],
                ins[i].type()));
      }
      out->ShareDataWith(ins[i]);
      out->set_lod(ins[i].lod());
    }
  }
};

class ReadOpMaker : public framework::OpProtoAndCheckerMaker {
 public:
  void Make() override {
    AddInput("Reader", "(ReaderHolder) The executed reader.");
    AddOutput("Out", "(phi::DenseTensor) The output data.").AsDuplicable();
    AddAttr<bool>(
        "throw_eof_exp",
        "If set true, an exception will be thrown when the Reader "
        "yields empty (which means there is no next data).\n"
        "NOTES: This flag must be true always. It will be set to false"
        " only when the data-balance is enabled in ParallelExecutor"
        " and it is set by ParallelExecutor instance, not users.")
        .SetDefault(true);
    AddAttr<bool>("infer_out", "").SetDefault(true);
    AddAttr<bool>("drop_last",
                  "Whether to drop last batches whose number is less than "
                  "actual used device number.")
        .SetDefault(true);
    AddComment(R"DOC(
      Read Operator

      Execute a given reader once and output data.
    )DOC");
  }
};

}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;
REGISTER_OPERATOR(
    read,
    ops::ReadOp,
    ops::ReadInferShape,
    ops::ReadOpMaker,
    paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
    paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>,
    ops::ReadInferVarType);
