def _reinit(self, dt_min=None, dt_max=None, normalize=False, **kwargs):
        """ Sets time kernel to custom value """
        assert len(self.l_max) == 3
        L = self.l_max[-3]
        # init = init or 'fourier'
        dt_min = dt_min or 2./L
        dt_max = dt_max or 2./L
        print(f"S4ND reinit args: {dt_min=} {dt_max=}", kwargs)
        kernel_args = {
            **self.kernel_args, **{
                'H': self.h,
                'N': self.n,
                'L': L,
                # 'init': init,
                'dt_min': dt_min,
                'dt_max': dt_max,
                # 'deterministic': True,
                'channels': self._kernel_channels,
                **kwargs,
            }
        }
        time_kernel = SSKernel(**kernel_args)
        if normalize:
            with torch.no_grad():
                time_kernel.kernel.C /= (0.5 * time_kernel.kernel.log_dt.exp()[:, None, None])
        self.kernel[-3] = time_kernel
 Sets time kernel to custom value 
analyze/convnexts4nd/src/models/sequence/modules/s4nd.py