code: def f_and_g_diagonal(self, t, y: Tensor):
      y = y[:, :-1]
      f, g, h = (
          self._base_f(t, y),
          self._base_g(t, y),
          self._base_h(t, y),
      )
      u = misc.stable_division(f - h, g)
      f_logqp = 0.5 * (u**2).sum(dim=1, keepdim=True)
      g_logqp = y.new_zeros(size=(y.size(0), 1))
      return torch.cat([f, f_logqp], dim=1), torch.cat(
          [g, g_logqp], dim=1
      )
  
imports: import abc
  import torch
  from torch import nn
  from .None import misc
  from ..settings import NOISE_TYPES, SDE_TYPES
  from ..types import Tensor
label_desc: Use image node_id 4 for calling the SDELogqp obj's underlying member method code with example usage: obj.f_and_g_diagonal(t, y) and returns: torch,  torch