A collection of datasets ready to use with TensorFlow.
TensorFlow Datasets is a collection of datasets ready to use with TensorFlow.
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 as tf import tensorflow_datasets as tfds # tfds works in both Eager and Graph modes tf.compat.v1.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"]Run in a Notebook
