tfr.keras.pipeline.NullDatasetBuilder
Stay organized with collections
Save and categorize content based on your preferences.
A no-op wrapper of datasets and signatures.
Inherits From: AbstractDatasetBuilder
tfr.keras.pipeline.NullDatasetBuilder(
train_dataset, valid_dataset, signatures=None
)
Example usage:
train_dataset = tf.data.Dataset(...)
valid_dataset = tf.data.Dataset(...)
dataset_builder = NullDatasetBuilder(train_dataset, valid_dataset)
Args |
train_dataset
|
A tf.data.Dataset for training.
|
valid_dataset
|
A tf.data.Dataset for validation.
|
signatures
|
A dict of signatures that formulate the model in functions
that render the input data with given types. When None, no signatures
assigned.
|
Methods
build_signatures
View source
build_signatures(
*arg, **kwargs
) -> Any
See AbstractDatasetBuilder
.
build_train_dataset
View source
build_train_dataset(
*arg, **kwargs
) -> tf.data.Dataset
See AbstractDatasetBuilder
.
build_valid_dataset
View source
build_valid_dataset(
*arg, **kwargs
) -> tf.data.Dataset
See AbstractDatasetBuilder
.
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2023-08-18 UTC.
[null,null,["Last updated 2023-08-18 UTC."],[],[],null,["# tfr.keras.pipeline.NullDatasetBuilder\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/ranking/blob/v0.5.3/tensorflow_ranking/python/keras/pipeline.py#L827-L863) |\n\nA no-op wrapper of datasets and signatures.\n\nInherits From: [`AbstractDatasetBuilder`](../../../tfr/keras/pipeline/AbstractDatasetBuilder) \n\n tfr.keras.pipeline.NullDatasetBuilder(\n train_dataset, valid_dataset, signatures=None\n )\n\n#### Example usage:\n\n train_dataset = tf.data.Dataset(...)\n valid_dataset = tf.data.Dataset(...)\n dataset_builder = NullDatasetBuilder(train_dataset, valid_dataset)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-----------------|--------------------------------------------------------------------------------------------------------------------------------------------|\n| `train_dataset` | A [`tf.data.Dataset`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset) for training. |\n| `valid_dataset` | A [`tf.data.Dataset`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset) for validation. |\n| `signatures` | A dict of signatures that formulate the model in functions that render the input data with given types. When None, no signatures assigned. |\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `build_signatures`\n\n[View source](https://github.com/tensorflow/ranking/blob/v0.5.3/tensorflow_ranking/python/keras/pipeline.py#L861-L863) \n\n build_signatures(\n *arg, **kwargs\n ) -\u003e Any\n\nSee `AbstractDatasetBuilder`.\n\n### `build_train_dataset`\n\n[View source](https://github.com/tensorflow/ranking/blob/v0.5.3/tensorflow_ranking/python/keras/pipeline.py#L853-L855) \n\n build_train_dataset(\n *arg, **kwargs\n ) -\u003e tf.data.Dataset\n\nSee `AbstractDatasetBuilder`.\n\n### `build_valid_dataset`\n\n[View source](https://github.com/tensorflow/ranking/blob/v0.5.3/tensorflow_ranking/python/keras/pipeline.py#L857-L859) \n\n build_valid_dataset(\n *arg, **kwargs\n ) -\u003e tf.data.Dataset\n\nSee `AbstractDatasetBuilder`."]]