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from sklearn.datasets import fetch_mldata


    

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mnist = fetch_mldata("MNIST original")


    

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X_train, X_test = mnist.data[:60000] / 255., mnist.data[60000:] / 255.


    

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y_train, y_test = mnist.target[:60000], mnist.target[60000:]


    

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np.save( "y_test.npy", y_test)


    

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np.save("X_test.npy", X_test)


    

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for i in xrange(10):
    np.save("X_train_%d.npy" % i, X_train[i * 6000:(i+1) * 6000])
    np.save("y_train_%d.npy" % i, y_train[i * 6000:(i+1) * 6000])


    

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X_Test.shape