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_index.yaml
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book_path: /datasets/_book.yaml
project_path: /datasets/_project.yaml
description: <!--no description-->
landing_page:
custom_css_path: /site-assets/css/style.css
rows:
- heading: A collection of datasets ready to use with TensorFlow.
items:
- description: >
TensorFlow Datasets is a collection of datasets ready to use with
TensorFlow.
All datasets are exposed as
<a href="https://www.tensorflow.org/api_docs/python/tf/data/Dataset">
<code>tf.data.Dataset</code>s
</a>,
enabling easy-to-use and high-performance
input pipelines.
To get started see the
<a href="./overview">TensorFlow Datasets Guide</a>.
- code_block: |
<pre class = "prettyprint">
import tensorflow as tf
import tensorflow_datasets as tfds
# tfds works in both Eager and Graph modes
tf.enable_eager_execution()
# See available datasets
print(tfds.list_builders())
# Construct a tf.data.Dataset
dataset = tfds.load(name="mnist", split=tfds.Split.TRAIN)
# Build your input pipeline
dataset = dataset.shuffle(1024).batch(32).prefetch(tf.data.experimental.AUTOTUNE)
for features in dataset.take(1):
image, label = features["image"], features["label"]
</pre>
{% dynamic if request.tld != 'cn' %}
<a class="colab-button" target="_blank" href="https://colab.research.google.com/github/tensorflow/datasets/blob/master/docs/_index.ipynb">Run in a <span>Notebook</span></a>
{% dynamic endif %}
- classname: devsite-landing-row-cards
items:
#- heading: Introducing TensorFlow Datasets
# image_path: /resources/images/tf-logo-card-16x9.png
# path: https://medium.com/tensorflow/REPLACE_ME
# buttons:
# - label: Read on TensorFlow blog
# path: https://medium.com/tensorflow/REPLACE_ME
- heading: TensorFlow Datasets on GitHub
image_path: /resources/images/github-card-16x9.png
path: https://github.com/tensorflow/datasets
buttons:
- label: View on GitHub
path: https://github.com/tensorflow/datasets