| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you 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. |
| |
| # pylint: disable=missing-docstring |
| from __future__ import print_function |
| |
| import numpy as np |
| import mxnet as mx |
| |
| |
| def get_mnist(): |
| """ Gets MNIST dataset """ |
| |
| np.random.seed(1234) # set seed for deterministic ordering |
| mnist_data = mx.test_utils.get_mnist() |
| X = np.concatenate([mnist_data['train_data'], mnist_data['test_data']]) |
| Y = np.concatenate([mnist_data['train_label'], mnist_data['test_label']]) |
| p = np.random.permutation(X.shape[0]) |
| X = X[p].reshape((X.shape[0], -1)).astype(np.float32)*5 |
| Y = Y[p] |
| return X, Y |
