code: def _affine_inv_mult(c, m):
      "Applies the inverse affine transform described in `m` to `c`."
      size = c.flow.size()
      h,w = c.size
      m[0,1] *= h/w
      m[1,0] *= w/h
      c.flow = c.flow.view(-1,2)
      a = torch.inverse(m[:2,:2].t())
      c.flow = torch.mm(c.flow - m[:2,2], a).view(size)
      return f _affine_inv_mult(c, m):
      "Applies the inverse affine transform described in `m` to `c`."
      size = c.flow.size()
      h,w = c.size
      m[0,1] *= h/w
      m[1,0] *= w/h
      c.flow = c.flow.view(-1,2)
      a = torch.inverse(m[:2,:2].t())
      c.flow = torch.mm(c.flow - m[:2,2], a).view(size)
      return c
docs: Applies the inverse affine transform described in `m` to `c`.