Method apply

tensorflow/python/data/ops/dataset_ops.py:1399–1428

Applies a transformation function to this dataset. `apply` enables chaining of custom `Dataset` transformations, which are represented as functions that take one `Dataset` argument and return a transformed `Dataset`. For example: ``` dataset = (dataset.map(lambda x: x ** 2

(self, transformation_func)

    return FilterDataset(self, predicate)

  def apply(self, transformation_func):
    """Applies a transformation function to this dataset.

    `apply` enables chaining of custom `Dataset` transformations, which are
    represented as functions that take one `Dataset` argument and return a
    transformed `Dataset`.

    For example:

    ```
    dataset = (dataset.map(lambda x: x ** 2)
               .apply(group_by_window(key_func, reduce_func, window_size))
               .map(lambda x: x ** 3))
    ```

    Args:
      transformation_func: A function that takes one `Dataset` argument and
        returns a `Dataset`.

    Returns:
      Dataset: The `Dataset` returned by applying `transformation_func` to this
          dataset.
    """
    dataset = transformation_func(self)
    if not isinstance(dataset, DatasetV2):
      raise TypeError(
          "`transformation_func` must return a Dataset. Got {}.".format(
              dataset))
    dataset._input_datasets = [self]  # pylint: disable=protected-access
    return dataset

  def window(self, size, shift=None, stride=1, drop_remainder=False):
    """Combines (nests of) input elements into a dataset of (nests of) windows.