TensorFlow Datasets: a collection of ready-to-use datasets.
TensorFlow Datasets is a collection of datasets ready to use, with TensorFlow or other Python ML frameworks, such as Jax.
All datasets are exposed as
tf.data.Datasets , enabling easy-to-use and high-performance input pipelines.
To get started see the guide and our list of datasets.
import tensorflow.compat.v2 as tf
import tensorflow_datasets as tfds
# Construct a tf.data.Dataset
ds = tfds.load('mnist', split='train', shuffle_files=True)
# Build your input pipeline
ds = ds.shuffle(1024).batch(32).prefetch(tf.data.experimental.AUTOTUNE)
for example in ds.take(1):
image, label = example["image"], example["label"]
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