code: def g_prod(self, t, y_aug, v):
      y, adj_y, _, requires_grad = self.get_state(t, y_aug, v)
      with torch.enable_grad():
          g_prod = self.forward_sde.g_prod(-t, y, v)
          return self._g_prod(g_prod, y, adj_y, requires_grad)
  
imports: import torch
  from .None import base_sde
  from .None import misc
  from ..settings import NOISE_TYPES, SDE_TYPES
  from ..types import Sequence, TensorOrTensors
label_desc: Use image node_id 13 for calling the AdjointSDE obj's underlying member method code with example usage: obj.g_prod(t, y_aug, v) and returns: self