'Data cardinality is ambiguous(Make sure all arrays contain the same number of samples)

I got my dataset from mnist dataset,

train_images = train_images.astype("float32")/255.0
test_images = test_images.astype("float32")/255.0

network.fit(train_images, train_labels, batch_size = 64, epochs = 10, verbose =2)
network.evaluate(test_images,test_labels, batch_size = 64, verbose=2)

I got this error during training

ValueError: Data cardinality is ambiguous:   x sizes: 10000   y sizes: 60000 Make sure all arrays contain the same number of samples .

Thanks

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'Data cardinality is ambiguous(Make sure all arrays contain the same number of samples)

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