def test_classif(self, cls_data):
X, Y = cls_data
Xc = X.cuda()
Yc = Y.cuda()
kernel = kernels.GaussianKernel(2.0)
torch.manual_seed(13)
np.random.seed(13)
def error_fn(t, p):
return 100 * torch.sum(t * p <= 0).to(
torch.float32) / t.shape[0], "c-err"
opt = FalkonOptions(use_cpu=False, keops_active="no", debug=True)
M = 500
flkc = InCoreFalkon(kernel=kernel,
penalty=1e-6,
M=M,
seed=10,
options=opt,
maxiter=20,
error_fn=error_fn)
flkc.fit(Xc, Yc)
cpreds = flkc.predict(Xc)
assert cpreds.device == Xc.device
err = error_fn(cpreds, Yc)[0]
assert err < 5
def test_fails_cpu_tensors(self, cls_data):
X, Y = cls_data
kernel = kernels.GaussianKernel(2.0)
opt = FalkonOptions(use_cpu=False, keops_active="no", debug=True)
flk = InCoreFalkon(kernel=kernel,
penalty=1e-6,
M=500,
seed=10,
options=opt)
with pytest.raises(ValueError):
flk.fit(X, Y)
flk.fit(X.cuda(), Y.cuda())
with pytest.raises(ValueError):
flk.predict(X)