common_nn.py 文件源码

def check_criterion_jacobian(self, criterion, input, target):
        eps = 1e-6
        self._forward_criterion(criterion, input, target)
        analytical_d_x = self._backward_criterion(criterion, input, target)
        numerical_d_x = deepcopy(analytical_d_x)

        input_t = iter_tensors(input)
        numerical_t = iter_tensors(numerical_d_x)
        for x, d_x in zip(input_t, numerical_t):
            x = x.view(-1)
            d_x = d_x.view(-1)
            for i in range(x.nelement()):
                original = x[i]
                x[i] = original + eps
                fx1 = self._forward_criterion(criterion, input, target)
                x[i] = original - eps
                fx2 = self._forward_criterion(criterion, input, target)
                deriv = (fx1 - fx2) / (2.*eps)
                d_x[i] = deriv
                x[i] = original

        # TODO: check structure
        analytical_t = iter_tensors(analytical_d_x)
        numerical_t = iter_tensors(numerical_d_x)
        self.assertLessEqual(
            max(a.add(-1, n).abs().max() for a, n in zip(analytical_t, numerical_t)),
            PRECISION
        )