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test_images_tf = test_images_tf.reshape(test_images_tf.shape[0],
test_images_tf.shape[2], 1)
predictions = modeltf.predict(test_images_tf)
correct = 0
for i, pred in enumerate(predictions):
if np.argmax(pred) == test_labels_tf[i]:
correct += 1
print('Test Accuracy of the model on the {} test images: {}%'.format(test_images_tf.shape[0],
100 * correct/test_images_tf.shape[0]))
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