I copied and pasted tensorflow's official Basic classification: Classify images of clothing code https://www.tensorflow.org/tutorials/keras/classification

import tensorflow as tf
    import numpy as np
    import matplotlib.pyplot as plt
    fashion_mnist = tf.keras.datasets.fashion_mnist
    (train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()

and ran it. Upon running it printed a load of gibberish and wouldn't stop (almost like when you accidentally put a print in a while loop):

Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-images-idx3-ubyte.gz
    
        8192/26421880 [..............................] - ETA: 6s
       98304/26421880 [..............................] - ETA: 14s
      106496/26421880 [..............................] - ETA: 27s
      417792/26421880 [..............................] - ETA: 10s
      425984/26421880 [..............................] - ETA: 13s

so I terminated it. The above is just a VERY small portion of what printed. I ran it again, only to get an error straight away.

line 7, in <module>
        (train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()
      File "C:\Users\david\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\keras\datasets\fashion_mnist.py", line 82, in load_data
        imgpath.read(), np.uint8, offset=16).reshape(len(y_train), 28, 28)
      File "C:\Users\david\AppData\Local\Programs\Python\Python38\lib\gzip.py", line 292, in read
        return self._buffer.read(size)
      File "C:\Users\david\AppData\Local\Programs\Python\Python38\lib\gzip.py", line 498, in read
        raise EOFError("Compressed file ended before the end-of-stream marker was reached")

I checked a similar question, deleted the dataset causing this error and ran it again. I waited out the gibberish it was printing out and waited for it to finish running, only for it to prematurely terminate after about 30 minutes with this error:

Traceback (most recent call last):
      File "C:\Users\david\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\keras\utils\data_utils.py", line 275, in get_file
        urlretrieve(origin, fpath, dl_progress)
      File "C:\Users\david\AppData\Local\Programs\Python\Python38\lib\urllib\request.py", line 286, in urlretrieve
        raise ContentTooShortError(
    urllib.error.ContentTooShortError: <urlopen error retrieval incomplete: got only 9191424 out of 26421880 bytes>

During handling of the above exception, another exception occurred:
 
    Traceback (most recent call last):
      File "C:\Users\david\Documents\DAVID\Documents\Education\Computer Science\Extra stuff\Machine learning\Neural networks\ep.2.py", line 7, in <module>
        (train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()
      File "C:\Users\david\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\keras\datasets\fashion_mnist.py", line 75, in load_data
        paths.append(get_file(fname, origin=base + fname, cache_subdir=dirname))
      File "C:\Users\david\AppData\Local\Programs\Python\Python38\lib\site-packages\tensorflow\python\keras\utils\data_utils.py", line 279, in get_file
        raise Exception(error_msg.format(origin, e.errno, e.reason))
    Exception: URL fetch failure on https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-images-idx3-ubyte.gz: None -- retrieval incomplete: got only 9191424 out of 26421880 bytes

I've tried deleting that dataset many times and each time I run the code the same thing happens again and again.

I can't find any forums or stack overflows on what to do when this happens, any help would be appreciated.

TL;DR what do I do to load a MNIST dataset when copying and pasting tensorflow's tutorial code leads to errors?

load_data function

tf.keras.datasets.fashion_mnist.load_data()

(x_train, y_train), (x_test, y_test) = fashion_mnist.load_data()
assert x_train.shape == (60000, 28, 28)
assert x_test.shape == (10000, 28, 28)
assert y_train.shape == (60000,)
assert y_test.shape == (10000,)

import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
# Load the fashion-mnist pre-shuffled train data and test data
(x_train, y_train), (x_test, y_test) = tf.keras.datasets.fashion_mnist.load_data()
print("x_train shape:", x_train.shape, "y_train shape:", y_train.shape)​

# example of loading the fashion mnist dataset
from matplotlib import pyplot
from keras.datasets import fashion_mnist
# load dataset
(trainX, trainy), (testX, testy) = fashion_mnist.load_data()
# summarize loaded dataset
print('Train: X=%s, y=%s' % (trainX.shape, trainy.shape))
print('Test: X=%s, y=%s' % (testX.shape, testy.shape))
# plot first few images
for i in range(9):
	# define subplot
	pyplot.subplot(330 + 1 + i)
	# plot raw pixel data
	pyplot.imshow(trainX, cmap=pyplot.get_cmap('gray'))
# show the figure
pyplot.show()