Function shuffle

tfjs-data/src/dataset.ts:431–454

* Pseudorandomly shuffles the elements of this dataset. This is done in a * streaming manner, by sampling from a given number of prefetched elements. * * ```js * const a = tf.data.array([1, 2, 3, 4, 5, 6]).shuffle(3); * await a.forEachAsync(e => console.log(e)); * ``` * * @pa

(bufferSize: number, seed?: string, reshuffleEachIteration = true)

   * @doc {heading: 'Data', subheading: 'Classes'}
   */
  shuffle(bufferSize: number, seed?: string, reshuffleEachIteration = true):
      Dataset<T> {
    if (bufferSize == null || bufferSize < 0) {
      if (this.size == null) {
        throw new RangeError(
            '`Dataset.shuffle()` requires bufferSize to be specified.');
      } else {
        throw new RangeError(
            '`Dataset.shuffle()` requires bufferSize to be specified.  ' +
            'If your data fits in main memory (for regular JS objects), ' +
            'and/or GPU memory (for `tf.Tensor`s), consider setting ' +
            `bufferSize to the dataset size (${this.size} elements)`);
      }
    }
    const base = this;
    const random = seedrandom.alea(seed || tf.util.now().toString());
    return datasetFromIteratorFn(async () => {
      let seed2 = random.int32();
      if (reshuffleEachIteration) {
        seed2 += random.int32();
      }
      return (await base.iterator()).shuffle(bufferSize, seed2.toString());
    }, this.size);
  }

  /**
   * Creates a `Dataset` with at most `count` initial elements from this