Keras: Error when downloading Fashion_MNIST Data - tensorflow

Question

I am trying to download data from Fashion MNIST, but it produces an error. Originally, it was downloading and working properly, but I had to terminate it because I had to turn off my computer. Once I opened the file up again, it gives me an error. I'm not sure what the problem is, but is it because I already downloaded some parts of the data once, and keras doesn't recognize that? I am using Jupyter notebook in a conda environment
Here is the link to the image:
https://i.stack.imgur.com/wLGDm.png

Answer 1

You have missed adding tf. to the line
fashion_mnist = keras.datasets.fashion_mnist
The below code works perfectly for me. Importing the fashion_mnist dataset has been outlined in tensorflow documention here.
Change your code to:
import tensorflow as tf
fashion_mnist = tf.keras.datasets.fashion_mnist
(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()
or, use the better way to do it below. This avoids creating an extra variable fashion_mnist:
import tensorflow as tf
(train_images, train_labels), (test_images, test_labels) = tf.keras.datasets.fashion_mnist.load_data()
I am using tensorflow 1.9.0, keras 2.2.2 and python 3.6.6 on Windows 10 x64 OS.

Answer 2

I know my pc well, I can't download anything larger than 2.7 MB (in terminal), due to WinError 8.
So I manually downloaded all packs from storage.google (since some packs are 25 MB).
Check the packs:
then I paste all packs to \datasets\fashion-mnist
The next time u run your code, it should be fixed.
Note : If u have VScode then just CTRL and click the link, then you can download it easily.

Answer 3

I had an error regarding the cURL connection, and by looking into the error message I was able to track the file where the URL was declared. In my case it was:
/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/datasets/fashion_mnist.py
At line 44 I have commented out the line:
# base = 'https://storage.googleapis.com/tensorflow/tf-keras-datasets/'
And declared a different base URL, which I had found looking into the documentation of the original dataset:
base = 'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/'
The download started immediately and gave no errors. Hope this helps.

Answer 4

This is because for some reason you have an incomplete download for the MNIST dataset.
You will have to manually delete the downloaded folder which usually resides in ~/.keras/datasets or any path specified by you relative to this path, in your case MNIST_data.
Go to : C:\Users\Username.keras\datasets
and then Delete the Dataset that you want to redownload or has the error
You should be good to go!

Answer 5

You can also manually add print for the path from which it is taking dataset ..
Ex: print(paths) in file fashion_mnist.py
with gzip.open(paths[3], 'rb') as imgpath:
print(paths) #debug print in fashion_mnist.py
x_test = np.frombuffer(
imgpath.read(), np.uint8, offset=16).reshape(len(y_test), 28, 28)
& from this path, remove the files & this will start to download fresh data ..

Answer 6

Change The base address with 'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/' as described previously. It works for me.
I was getting error of Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz
Traceback (most recent call last):
File "C:\Users\AsadA\AppData\Local\Programs\Python\Python38\lib\site-packages\numpy\lib\npyio.py", line 448, in load
return pickle.load(fid, **pickle_kwargs)
EOFError: Ran out of input
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\AsadA\AppData\Local\Programs\Python\Python38\lib\site-packages\numpy\lib\npyio.py", line 450, in load
raise IOError(
OSError: Failed to interpret file 'C:\\Users\\AsadA\\.keras\\datasets\\mnist.npz' as a pickle"**
GO TO FILE C:\Users\AsadA\AppData\Local\Programs\Python\Python38\Lib\site-packages\tensorflow\python\keras\datasets (In my Case) and follow the instructions: