from mnist import MNIST
import numpy as np
mndata = MNIST('g')
images, labels = mndata.load_training()
X = []
s = 0
for i in images:
    print(s)
    for r in i:
        X.append([r / 255])
    s += 1
print(X[0])

fb13811cd61a16bb83454811b94f7d84eeca13bf
<mask token>

<mask token>
for i in images:
    print(s)
    for r in i:
        X.append([r / 255])
    s += 1
print(X[0])

<mask token>
mndata = MNIST('g')
images, labels = mndata.load_training()
X = []
s = 0
for i in images:
    print(s)
    for r in i:
        X.append([r / 255])
    s += 1
print(X[0])

from mnist import MNIST
import numpy as np
mndata = MNIST('g')
images, labels = mndata.load_training()
X = []
s = 0
for i in images:
    print(s)
    for r in i:
        X.append([r / 255])
    s += 1
print(X[0])
