tf.compat.v1.data.make_one_shot_iterator | TensorFlow v2.16.1 (original) (raw)
tf.compat.v1.data.make_one_shot_iterator
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Creates an iterator for elements of dataset.
tf.compat.v1.data.make_one_shot_iterator(
dataset: tf.compat.v1.data.Dataset
) -> Union[iterator_ops.Iterator, iterator_ops.OwnedIterator]
Migrate to TF2
This is a legacy API for consuming dataset elements and should only be used during transition from TF 1 to TF 2. Note that using this API should be a transient state of your code base as there are in general no guarantees about the interoperability of TF 1 and TF 2 code.
In TF 2 datasets are Python iterables which means you can consume their elements using for elem in dataset: ... or by explicitly creating iterator via iterator = iter(dataset) and fetching its elements viavalues = next(iterator).
Description
Used in the notebooks
| Used in the tutorials |
|---|
| Exploring the TF-Hub CORD-19 Swivel Embeddings Graph-based Neural Structured Learning in TFX Preprocessing data with TensorFlow Transform |
| Args | |
|---|---|
| dataset | A tf.data.Dataset. |
| Returns |
|---|
| A tf.data.Iterator for elements of dataset. |
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Last updated 2024-04-26 UTC.