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# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""MNIST handwritten digits dataset.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.python.keras.utils.data_utils import get_file
from tensorflow.python.util.tf_export import tf_export
@tf_export('keras.datasets.mnist.load_data')
def load_data(path='mnist.npz'):
"""Loads the MNIST dataset.
Arguments:
path: path where to cache the dataset locally
(relative to ~/.keras/datasets).
Returns:
Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
License:
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.](
https://creativecommons.org/licenses/by-sa/3.0/)
"""
origin_folder = 'https://storage.googleapis.com/tensorflow/tf-keras-datasets/'
path = get_file(
path,
origin=origin_folder + 'mnist.npz',
file_hash='8a61469f7ea1b51cbae51d4f78837e45')
with np.load(path) as f:
x_train, y_train = f['x_train'], f['y_train']
x_test, y_test = f['x_test'], f['y_test']
return (x_train, y_train), (x_test, y_test)
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