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