def test_frelu(self):
# Generate inputs
x = torch.rand(2, 8, 19, 19)
# Optional argument testing
with torch.no_grad():
out = activation.FReLU(8)(x)
self.assertEqual(out.size(), x.size())
self.assertFalse(torch.equal(out, x))
def test_frelu():
mod = activation.FReLU(8).eval()
with torch.no_grad():
_test_activation_function(mod.forward, (4, 8, 32, 32))
assert len(repr(mod).split('\n')) == 4