TensorFlow 1 version | View source on GitHub |
Splits elements of a dataset into multiple elements on the batch dimension. (deprecated)
tf.data.experimental.unbatch()
For example, if elements of the dataset are shaped [B, a0, a1, ...]
,
where B
may vary for each input element, then for each element in the
dataset, the unbatched dataset will contain B
consecutive elements
of shape [a0, a1, ...]
.
# NOTE: The following example uses `{ ... }` to represent the contents
# of a dataset.
a = { ['a', 'b', 'c'], ['a', 'b'], ['a', 'b', 'c', 'd'] }
a.apply(tf.data.experimental.unbatch()) == {
'a', 'b', 'c', 'a', 'b', 'a', 'b', 'c', 'd'}
Returns | |
---|---|
A Dataset transformation function, which can be passed to
tf.data.Dataset.apply .
|