| import os | |
| import numpy as np | |
| from sklearn.datasets import fetch_mldata | |
| def get_mnist(): | |
| np.random.seed(1234) # set seed for deterministic ordering | |
| data_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__))) | |
| data_path = os.path.join(data_path, '../../data') | |
| mnist = fetch_mldata('MNIST original', data_home=data_path) | |
| p = np.random.permutation(mnist.data.shape[0]) | |
| X = mnist.data[p].astype(np.float32)*0.02 | |
| Y = mnist.target[p] | |
| return X, Y |