EVOLUTION-MANAGER

Edit File: record_yielder.h

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
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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,
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==============================================================================*/

#ifndef TENSORFLOW_CORE_KERNELS_RECORD_YIELDER_H_
#define TENSORFLOW_CORE_KERNELS_RECORD_YIELDER_H_

#include <atomic>
#include <random>
#include <string>
#include <vector>

#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/core/notification.h"
#include "tensorflow/core/lib/core/threadpool.h"
#include "tensorflow/core/platform/macros.h"
#include "tensorflow/core/platform/thread_annotations.h"

namespace tensorflow {

// RecordYielder produces value records from a set of tfrecord files
// in a random order.
//
// It guarantees that:
//   1) all records in tfrecords are yielded within every epoch;
//   2) each record is yielded only once within every epoch;
//   3) the order in which records are yielded is highly randomized.
//   4) the peak memory usage is roughly avg record size *
//      (opts.bufsize + opts.parallelism * 16).
//
// Usage example:
//   RecordYielder::Options opts;
//   opts.file_pattern = "input-*";
//   opts.seed = 301;
//   opts.bufsize = 1000000;    // A randomized buffer with 1M records.
//   opts.parallelism = 8;      // Uses 8 tfrecord iterators to iterate
//                              // through all files.
//   RecordYielder yielder(opts);
//   string val;
//   while (true) {
//     yielder.YieldOne(&val);
//     // process val
//   }
//
// RecordYielder can be accessed by multiple threads concurrently.
class RecordYielder {
 public:
  struct Options {
    // Glob pattern for tfrecords.
    string file_pattern;

// Random seed. It determines how data files are shuffled and how
    // records are shuffled.
    int64 seed = 0;

// Each epoch, all files are first shuffled according to the
    // random seed and the epoch number, and then all files are
    // left-shifted by file_shuffle_shift_ratio * num_files slots.  If
    // file_shuffle_shift_ratio is not within [0, 1), the
    // implementation clip it to [0, 1).
    float file_shuffle_shift_ratio = 0;

// Randomization buffer keeps these many records.
    uint64 bufsize = 1;

// Uses these many concurrent tfrecord iterators to iterate through
    // tfrecords.
    int32 parallelism = 1;

string compression_type;
  };

explicit RecordYielder(OpKernelConstruction* context,
                         const RecordYielder::Options& opts);
  ~RecordYielder();

RecordYielder(const RecordYielder&) = delete;
  RecordYielder& operator=(const RecordYielder&) = delete;

// Yields one 'value'.
  Status YieldOne(tstring* value);

// Returns the current epoch number.
  int64 current_epoch() const { return epoch_; }

private:
  typedef RecordYielder ME;

Options opts_;

// Backgrounds threads. Owned.
  thread::ThreadPool* thread_;

// Epoch number.
  std::atomic<int64> epoch_;

mutex mu_;

// Turned to true when this is deleted.
  bool stop_ TF_GUARDED_BY(mu_) = false;
  Status status_ TF_GUARDED_BY(mu_);

// PRG used for randomization.
  std::mt19937_64 rnd_ TF_GUARDED_BY(mu_);

// Randomization buffer.
  std::vector<string> buf_ TF_GUARDED_BY(mu_);

// True iff we are draining an epoch.
  bool epoch_end_ = false;

int64 num_records_added_in_epoch_ = 0;
  int64 num_records_yielded_in_epoch_ = 0;

// Trigger when the main loop has exited.
  Notification main_loop_done_;

// condition_variables.
  condition_variable buf_empty_;
  bool BufEmpty() const TF_SHARED_LOCKS_REQUIRED(mu_) {
    return stop_ || buf_.empty();
  }

condition_variable buf_not_full_;
  bool BufNotFull() const TF_SHARED_LOCKS_REQUIRED(mu_) {
    return stop_ || buf_.size() < opts_.bufsize;
  }

condition_variable buf_enough_;
  bool BufEnough() const TF_SHARED_LOCKS_REQUIRED(mu_) {
    // NOTE: Unless we are finishing an epoch, we want to make sure
    // the buf_ contains enough randomized elements before yielding
    // any.
    return stop_ || !status_.ok() || (epoch_end_ && !buf_.empty()) ||
           (!epoch_end_ &&
            buf_.size() >= std::max<uint64>(1, opts_.bufsize / 2));
  }

void MainLoop();
  struct Shard;
  void ShardLoop(Shard* shard);
  bool ShouldFinish(const Status& s);
  bool Add(std::vector<string>* values);
};

}  // namespace tensorflow

#endif  // TENSORFLOW_CORE_KERNELS_RECORD_YIELDER_H_