/* 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. */

#pragma once

#include <cstdint>
#include <memory>
#include <random>
#include <vector>

#include "paddle/fluid/platform/enforce.h"

namespace paddle {
namespace operators {
namespace math {

// TODO(wanghaoshuang): Support for GPU

/**
 * Sample integers from [0, range).
 */
class Sampler {
 public:
  explicit Sampler(int64_t range, unsigned int seed = 0UL) : range_(range) {
    PADDLE_ENFORCE_GT(
        range,
        0,
        platform::errors::InvalidArgument(
            "Range should be greater than 0, but recevied %d.", range));
    if (seed == 0) {
      std::random_device r;
      seed_ = r();
    } else {
      seed_ = seed;
    }
  }

  virtual ~Sampler();

  // Sample a single value
  virtual int64_t Sample() const = 0;

  // The probability that a single call to Sample() returns the given value.
  virtual float Probability(int64_t value) const = 0;

  int64_t range() { return range_; }

 protected:
  const int64_t range_;
  unsigned int seed_;
};

/**
 * Sample integers from [0, range).
 * And the distribution function is:
 * P(x) = 1 / range
 */
class UniformSampler : public Sampler {
 public:
  explicit UniformSampler(int64_t range, unsigned int seed = 0UL);

  ~UniformSampler() override {}

  int64_t Sample() const override;

  float Probability(int64_t value) const override;

 private:
  const float inv_range_;
  std::shared_ptr<std::mt19937_64> random_engine_;
  std::shared_ptr<std::uniform_int_distribution<>> dist_;
};

/**
 * Sample integers from [0, range).
 * And the distribution function is:
 * P(x) = (1/ln(range+1)) * ln(1 + 1/(x + 1))
 */
class LogUniformSampler : public Sampler {
 public:
  explicit LogUniformSampler(int64_t range, unsigned int seed = 0UL);

  ~LogUniformSampler() override {}

  int64_t Sample() const override;

  float Probability(int64_t value) const override;

 private:
  const float log_range_;
  std::shared_ptr<std::mt19937_64> random_engine_;
  std::shared_ptr<std::uniform_real_distribution<>> dist_;
};

/**
 * Sample integers from [0, range) from custom distribution.
 */
class CustomSampler : public Sampler {
 public:
  explicit CustomSampler(int64_t range,
                         const float* probabilities,
                         const int* alias,
                         const float* alias_probabilities,
                         unsigned int seed = 0UL);

  ~CustomSampler() override {}

  int64_t Sample() const override;

  float Probability(int64_t value) const override;

 private:
  const float* alias_probs_;
  const int* alias_;
  const float* probs_;
  const int exceptional_val = -1;
  std::shared_ptr<std::mt19937_64> random_engine_;
  std::shared_ptr<std::uniform_real_distribution<>> real_dist_;
  std::shared_ptr<std::uniform_int_distribution<>> int_dist_;
};

}  // namespace math
}  // namespace operators
}  // namespace paddle
