tf.keras.datasets.mnist.load_data

Loads the MNIST dataset.

tf.keras.datasets.mnist.load_data(
    path='mnist.npz'
)

This is a dataset of 60,000 28x28 grayscale images of the 10 digits, along with a test set of 10,000 images. More info can be found at the MNIST homepage.

path path where to cache the dataset locally (relative to ~/.keras/datasets).

Tuple of NumPy arrays: (x_train, y_train), (x_test, y_test).

x_train: uint8 NumPy array of grayscale image data with shapes (60000, 28, 28), containing the training data. Pixel values range from 0 to 255.

y_train: uint8 NumPy array of digit labels (integers in range 0-9) with shape (60000,) for the training data.

x_test: uint8 NumPy array of grayscale image data with shapes (10000, 28, 28), containing the test data. Pixel values range from 0 to 255.

y_test: uint8 NumPy array of digit labels (integers in range 0-9) with shape (10000,) for the test data.

Example:

(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()
assert x_train.shape == (60000, 28, 28)
assert x_test.shape == (10000, 28, 28)
assert y_train.shape == (60000,)
assert y_test.shape == (10000,)

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.