Module neuralops.tests.test_softcap

Unit tests for softcap function.

Functions

def test_softcap_bounds()

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def test_softcap_bounds():
    scores = torch.randn(10, 10) * 1000.0
    out = softcap(scores, cap=50.0)
    assert (out.abs() <= 50.0).all()

def test_softcap_gradients()

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def test_softcap_gradients():
    x = torch.randn(5, 5, requires_grad=True)
    out = softcap(x, cap=20.0)
    out.sum().backward()
    assert x.grad is not None
    assert not torch.isnan(x.grad).any()

def test_softcap_monotonicity()

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def test_softcap_monotonicity():
    x = torch.linspace(-100, 100, 200)
    out = softcap(x, cap=30.0)
    diff = out[1:] - out[:-1]
    assert (diff >= 0).all()