/* Copyright 2015 The TensorFlow 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.
==============================================================================*/

#ifndef TENSORFLOW_STREAM_EXECUTOR_RNG_H_
#define TENSORFLOW_STREAM_EXECUTOR_RNG_H_

#include <limits.h>
#include <complex>

#include "tensorflow/stream_executor/platform/logging.h"
#include "tensorflow/stream_executor/platform/port.h"

namespace stream_executor {

class Stream;
template <typename ElemT>
class DeviceMemory;

namespace rng {

// Random-number-generation support interface -- this can be derived from a GPU
// executor when the underlying platform has an RNG library implementation
// available. See StreamExecutor::AsRng().
// When a seed is not specified, the backing RNG will be initialized with the
// default seed for that implementation.
//
// Thread-hostile: see StreamExecutor class comment for details on
// thread-hostility.
class RngSupport {
 public:
  static const int kMinSeedBytes = 16;
  static const int kMaxSeedBytes = INT_MAX;

  // Releases any random-number-generation resources associated with this
  // support object in the underlying platform implementation.
  virtual ~RngSupport() {}

  // Populates a GPU memory allocation with random values appropriate for the
  // DeviceMemory element type; i.e. populates DeviceMemory<float> with random
  // float values.
  virtual bool DoPopulateRandUniform(Stream *stream,
                                     DeviceMemory<float> *v) = 0;
  virtual bool DoPopulateRandUniform(Stream *stream,
                                     DeviceMemory<double> *v) = 0;
  virtual bool DoPopulateRandUniform(Stream *stream,
                                     DeviceMemory<std::complex<float>> *v) = 0;
  virtual bool DoPopulateRandUniform(Stream *stream,
                                     DeviceMemory<std::complex<double>> *v) = 0;

  // Populates a GPU memory allocation with random values sampled from a
  // Gaussian distribution with the given mean and standard deviation.
  virtual bool DoPopulateRandGaussian(Stream *stream, float mean, float stddev,
                                      DeviceMemory<float> *v) {
    LOG(ERROR)
        << "platform's random number generator does not support gaussian";
    return false;
  }
  virtual bool DoPopulateRandGaussian(Stream *stream, double mean,
                                      double stddev, DeviceMemory<double> *v) {
    LOG(ERROR)
        << "platform's random number generator does not support gaussian";
    return false;
  }

  // Specifies the seed used to initialize the RNG.
  // This call does not transfer ownership of the buffer seed; its data should
  // not be altered for the lifetime of this call. At least 16 bytes of seed
  // data must be provided, but not all seed data will necessarily be used.
  // seed: Pointer to seed data. Must not be null.
  // seed_bytes: Size of seed buffer in bytes. Must be >= 16.
  virtual bool SetSeed(Stream *stream, const uint8 *seed,
                       uint64 seed_bytes) = 0;

 protected:
  static bool CheckSeed(const uint8 *seed, uint64 seed_bytes);
};

}  // namespace rng
}  // namespace stream_executor

#endif  // TENSORFLOW_STREAM_EXECUTOR_RNG_H_
