See `window_dataset()` for more details.
(self, input_dataset, size, shift, stride, drop_remainder)
| 3770 | """A dataset that creates window datasets from the input elements.""" |
| 3771 | |
| 3772 | def __init__(self, input_dataset, size, shift, stride, drop_remainder): |
| 3773 | """See `window_dataset()` for more details.""" |
| 3774 | self._input_dataset = input_dataset |
| 3775 | self._size = ops.convert_to_tensor(size, dtype=dtypes.int64, name="size") |
| 3776 | self._shift = ops.convert_to_tensor(shift, dtype=dtypes.int64, name="shift") |
| 3777 | self._stride = ops.convert_to_tensor( |
| 3778 | stride, dtype=dtypes.int64, name="stride") |
| 3779 | self._drop_remainder = ops.convert_to_tensor( |
| 3780 | drop_remainder, dtype=dtypes.bool, name="drop_remainder") |
| 3781 | self._structure = nest.pack_sequence_as( |
| 3782 | get_legacy_output_classes(input_dataset), [ |
| 3783 | DatasetSpec( # pylint: disable=g-complex-comprehension |
| 3784 | structure.convert_legacy_structure( |
| 3785 | output_type, output_shape, output_class)) |
| 3786 | for output_class, output_shape, output_type in zip( |
| 3787 | nest.flatten(get_legacy_output_classes(input_dataset)), |
| 3788 | nest.flatten(get_legacy_output_shapes(input_dataset)), |
| 3789 | nest.flatten(get_legacy_output_types(input_dataset))) |
| 3790 | ]) |
| 3791 | variant_tensor = gen_dataset_ops.window_dataset( |
| 3792 | input_dataset._variant_tensor, # pylint: disable=protected-access |
| 3793 | self._size, |
| 3794 | self._shift, |
| 3795 | self._stride, |
| 3796 | self._drop_remainder, |
| 3797 | **self._flat_structure) |
| 3798 | super(WindowDataset, self).__init__(input_dataset, variant_tensor) |
| 3799 | |
| 3800 | @property |
| 3801 | def element_spec(self): |
nothing calls this directly
no test coverage detected