def test_onehot_like():
a = np.array([0.1, 0.5, 0.7, 0.4])
o = onehot_like(a, 2)
assert o.shape == a.shape
assert o.dtype == a.dtype
assert np.all(o[:2] == 0)
assert o[2] == 1
assert np.all(o[3:] == 0)
o = onehot_like(a, 3, value=-77.5)
assert o.shape == a.shape
assert o.dtype == a.dtype
assert np.all(o[:3] == 0)
assert o[3] == -77.5
assert np.all(o[4:] == 0)
def best_other_class(logits, exclude):
"""
Returns the index of the largest logit, ignoring the class that
is passed as `exclude`.
"""
other_logits = logits - onehot_like(logits, exclude, value=np.inf)
return np.argmax(other_logits)