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. My question is that, are there any function or code that can let me directly import mnist data set that has been manually downloaded. Thanks.

This is the modified 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)

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)

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. My question is that, are there any function or code that can let me directly import mnist data set that has been manually downloaded. Thanks.

This is the modified approach

import sys
import pickle
import gzip
f = gzip.open('/data/dsp_emerging/ugwz/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)

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. My question is that, are there any function or code that can let me directly import mnist data set that has been manually downloaded. Thanks.

This is the modified 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)

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. My question is that, are there any function or code that can let me directly import mnist data set that has been manually downloaded. Thanks.

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. My question is that, are there any function or code that can let me directly import mnist data set that has been manually downloaded. Thanks.

This is the modified approach

import sys
import pickle
import gzip
f = gzip.open('/data/dsp_emerging/ugwz/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)