def test_one_hot():
skip_if_no_data()
data = icml07.MNIST_rotated_background(which_set='train', one_hot=True,
split=(100, 100, 100))
assert data.y.shape[1] == 10 # MNITS hast 10 classes
data = icml07.Rectangles(which_set='train', one_hot=True,
split=(100, 100, 100))
assert data.y.shape[1] == 2 # Two classes
def test_split():
skip_if_no_data()
n_train = 100
n_valid = 200
n_test = 300
data = icml07.MNIST_rotated_background(which_set='train',
split=(n_train, n_valid, n_test))
assert data.X.shape[0] == n_train, "Unexpected size of train set"
assert data.y.shape[0] == n_train, "Unexpected size of train set"
data = icml07.MNIST_rotated_background(which_set='valid',
split=(n_train, n_valid, n_test))
assert data.X.shape[0] == n_valid, "Unexpected size of validation set"
assert data.y.shape[0] == n_valid, "Unexpected size of validation set"
data = icml07.MNIST_rotated_background(which_set='test',
split=(n_train, n_valid, n_test))
assert data.X.shape[0] == n_test, "Unexpected size of test set"
assert data.y.shape[0] == n_test, "Unexpected size of test set"
def test_MNIST_rot_back():
skip_if_no_data()
data = icml07.MNIST_rotated_background(which_set='train')
data = icml07.MNIST_rotated_background(which_set='valid')
data = icml07.MNIST_rotated_background(which_set='test')