// Copyright (c) 2019 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 "paddle/fluid/framework/generator.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_version_registry.h"

namespace paddle {
namespace operators {
using Tensor = framework::Tensor;

static int get_seed(const framework::ExecutionContext& context) {
  int user_seed = context.Attr<int>("seed");
  bool deterministic = context.Attr<bool>("deterministic");

  int seed = 0;
  if (!deterministic) {
    // NOTE: fixed seed should only be used in unittest or for debug.
    // Guarantee to use random seed in training.
    if (user_seed != 0) {
      seed = user_seed;
    } else {
      std::random_device rnd;
      seed = rnd();
    }
  } else {
    std::string name = context.Attr<std::string>("rng_name");
    auto rng = framework::GetRandomSeedGenerator(name);
    do {  // NOTE(wangxi): cpu dropout will use random seed if seed == 0
      seed = static_cast<int>(rng->Random64());
    } while (seed == 0);
  }
  return seed;
}

template <typename DeviceContext, typename T>
class CPUSeedKernel : public framework::OpKernel<T> {
 public:
  void Compute(const framework::ExecutionContext& context) const override {
    auto* out = context.Output<Tensor>("Out");
    auto* out_data = out->mutable_data<T>(context.GetPlace());
    out_data[0] = get_seed(context);
  }
};

}  // namespace operators
}  // namespace paddle