code: def dg_ga_jvp_column_sum_v1(self, t, y, a):
      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)
          ga = torch.bmm(g, a)
          dg_ga_jvp = [
              misc.jvp(
                  outputs=g[..., col_idx],
                  inputs=y,
                  grad_inputs=ga[..., col_idx],
                  retain_graph=True,
                  create_graph=requires_grad,
                  allow_unused=True,
              )[0]
              for col_idx in range(g.size(-1))
          ]
          dg_ga_jvp = sum(dg_ga_jvp)
      return dg_ga_jvp
  
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 13 for calling the ForwardSDE obj's underlying member method code with example usage: obj.dg_ga_jvp_column_sum_v1(t, y, a) and returns: dg_ga_jvp