code: def g_prod_and_gdg_prod_diagonal(self, t, y, v1, v2):
      requires_grad = torch.is_grad_enabled()
      with torch.enable_grad():
          y = y if y.requires_grad else y.detach().requires_grad_(True)
          g = self.g(t, y)
          (vg_dg_vjp,) = misc.vjp(
              outputs=g,
              inputs=y,
              grad_outputs=g * v2,
              retain_graph=True,
              create_graph=requires_grad,
              allow_unused=True,
          )
      return self.prod(g, v1), vg_dg_vjp
  
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 11 for calling the ForwardSDE obj's underlying member method code with example usage: obj.g_prod_and_gdg_prod_diagonal(t, y, v1, v2) and returns: self,  vg_dg_vjp