def testSmoothSVMth_functional(self):
F = Topk_Smooth_SVM(self.labels, self.k, self.tau)
res_th = F(V(self.x), V(self.y))
res_py = svm_topk_smooth_py_1(V(self.x), V(self.y), self.tau, self.k)
assert_all_close(res_th, res_py)
def testSmoothSVMth_loss_scales(self):
svm_topk_smooth_th = SmoothTopkSVM(self.n_classes, tau=self.tau, k=self.k)
for scale in (1e-4, 1e-3, 1e-2, 1e-1, 1e0, 1e1, 1e2, 1e3):
x = self.x * scale
res_th = svm_topk_smooth_th(V(x), V(self.y))
res_py = svm_topk_smooth_py_1(V(x), V(self.y), self.tau, self.k).mean()
assert_all_close(res_th, res_py)
def testSmoothSVMth_loss(self):
for k in range(2, self.k + 1):
svm_topk_smooth_th = SmoothTopkSVM(self.n_classes, tau=self.tau, k=k)
res_th = svm_topk_smooth_th(V(self.x), V(self.y))
res_py = svm_topk_smooth_py_1(V(self.x), V(self.y),
self.tau, k).mean()
assert_all_close(res_th, res_py)
def testSmoothSVMpy(self):
res_py_1 = svm_topk_smooth_py_1(V(self.x), V(self.y), self.tau, self.k)
res_py_2 = svm_topk_smooth_py_2(V(self.x), V(self.y), self.tau, self.k)
assert_all_close(res_py_1, res_py_2)