Function skip

tfjs-data/src/dataset.ts:384–404

* Creates a `Dataset` that skips `count` initial elements from this dataset. * * ```js * const a = tf.data.array([1, 2, 3, 4, 5, 6]).skip(3); * await a.forEachAsync(e => console.log(e)); * ``` * * @param count: The number of elements of this dataset that should be skipped *

(count: number)

   * @doc {heading: 'Data', subheading: 'Classes'}
   */
  skip(count: number): Dataset<T> {
    const base = this;
    let size;
    if (this.size != null && count >= 0 && this.size >= count) {
      // If the size of this dataset is greater than count, the new dataset's
      // size is current size minus skipped size.This also covers the case that
      // current size is infinity.
      size = this.size - count;
    } else if (
        this.size != null &&
        (this.size < count || count === undefined || count < 0)) {
      // If the size of this dataset is smaller than count, or count is
      // undefined or negative, skips the entire dataset and the new size is 0.
      size = 0;
    } else {
      // If the size of this dataset is null, the new dataset's size is null.
      size = null;
    }
    return datasetFromIteratorFn(
        async () => (await base.iterator()).skip(count), size);
  }

  // TODO(soergel): deep sharded shuffle, where supported