How can I import the MNIST dataset that has been manually downloaded?

Question

I have been experimenting with a Keras example, which needs to import MNIST data

from keras.datasets import mnist
import numpy as np
(x_train, _), (x_test, _) = mnist.load_data()

It generates error messages such as Exception: URL fetch failure on https://s3.amazonaws.com/img-datasets/mnist.pkl.gz: None -- [Errno 110] Connection timed out

It should be related to the network environment I am using. Is there any function or code that can let me directly import the MNIST data set that has been manually downloaded?

I tried the following approach

import sys
import pickle
import gzip
f = gzip.open('/data/mnist.pkl.gz', 'rb')
  if sys.version_info < (3,):
    data = pickle.load(f)
else:
    data = pickle.load(f, encoding='bytes')
f.close()
import numpy as np
(x_train, _), (x_test, _) = data

Then I get the following error message

Traceback (most recent call last):
File "test.py", line 45, in <module>
(x_train, _), (x_test, _) = data
ValueError: too many values to unpack (expected 2)

Answer 1

Well, the keras.datasets.mnist file is really short. You can manually simulate the same action, that is:

1. Download a dataset from https://s3.amazonaws.com/img-datasets/mnist.pkl.gz

2. .

   import gzip
   f = gzip.open('mnist.pkl.gz', 'rb')
   if sys.version_info < (3,):
       data = cPickle.load(f)
   else:
       data = cPickle.load(f, encoding='bytes')
   f.close()
   (x_train, _), (x_test, _) = data