A function to load numpy arrays from the MNIST data files.

mnist.py

""" A function that can read MNIST's idx file format into numpy arrays.

    The MNIST data files can be downloaded from here:
    
    http://yann.lecun.com/exdb/mnist/

    This relies on the fact that the MNIST dataset consistently uses
    unsigned char types with their data segments.
"""

import struct

import numpy as np

def read_idx(filename):
    with open(filename, 'rb') as f:
        zero, data_type, dims = struct.unpack('>HBB', f.read(4))
        shape = tuple(struct.unpack('>I', f.read(4))[0] for d in range(dims))
        return np.fromstring(f.read(), dtype=np.uint8).reshape(shape)

The original file "train-images-idx3-ubyte.gz" is 9912422 bytes. It is much smaller than 282860000. We need to unzip the file first in order to use it. Some software 7zip or Winrar will help you to do this. Otherwise you will face the problem "cannot reshape array of size 9912386 into shape (2055376946,226418,1634299437,1768776039,1702047337,1685599021,1969387892,1694559388)". (written for some students who is as puzzled as me, when they are doing their homework)

Python can automatically handle gzip files, just add:

import gzip

Then change

with open(filename, 'rb') as f:

to:

with gzip.open(filename) as f:

Thanks a lot dude! It is interesting that the default encoding was high-endian for NON-intel processors... since in my mind most people ARE using Intel processors... Anyway, thanks for the gist!