code: def deeplift_grad(module, grad_input, grad_output):
      
      # first, get the module type
      module_type = module.__class__.__name__
      # first, check the module is supported
      if module_type in op_handler:
          if op_handler[module_type].__name__ not in ['passthrough', 'linear_1d']:
              return op_handler[module_type](module, grad_input, grad_output)
      else:
          print('Warning: unrecognized nn.Module: {}'.format(module_type))
          return grad_input
docs: The backward hook which computes the deeplift
      gradient for an nn.Module