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def open_train_data(path):
train = []
with open(path, 'r') as f:
reader = csv.reader(f)
lines = list(reader)
for line in tqdm(lines[1:]):
label = line[0]
image = np.array([x for x in line[1:]])
image = image.astype('float32')
# Format the data to 28x28x1 (in grey scale)
image = np.reshape(image, (28, 28, 1))
train.append([image, label])
return np.array(train)
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