|TensorFlow 1 version||View source on GitHub|
Loads the MNIST dataset.
Used in the guide:
- Save and serialize models with Keras
- Eager execution
- Better performance with tf.function and AutoGraph
- Keras custom callbacks
- Writing custom layers and models with Keras
Used in the tutorials:
- Save and load a model using a distribution strategy
- Convolutional Variational Autoencoder
- Deep Convolutional Generative Adversarial Network
- Save and load models
path: path where to cache the dataset locally (relative to ~/.keras/datasets).
Tuple of Numpy arrays:
(x_train, y_train), (x_test, y_test).
Yann LeCun and Corinna Cortes hold the copyright of MNIST dataset, which is a derivative work from original NIST datasets. MNIST dataset is made available under the terms of the Creative Commons Attribution-Share Alike 3.0 license.