load_test_data.py

import cupy as np
import pickle

def load_test_data(data_file_path, packed_file_path):
  # Speed up the getting data part by being smart and not wasting time on parsing the test.csv file an cache it as a pickle so that it can be imported very quickly. saves 6s
  try:
    with open(packed_file_path, "rb") as f:
      data = pickle.load(f)
      return data["x"]
  except:
    data = np.genfromtxt(data_file_path, delimiter=',', skip_header=1, dtype=np.float64)
    data.reshape((data.shape[0], 784, 1))
    with open(packed_file_path, "wb") as f:
      pickle.dump(data, f)
    return data