code: def spectral_norm_backward(
      grad_inputs,
      inputs,
      input_shapes,
      outputs,
      output_shapes,
      dim=0,
      itr=1,
      eps=1e-12,
      test=False,
      output_u=False,
  ):
      """
      Args:
        grad_inputs (list of :obj:`nnabla.Variable`): Propagated grads to this backward function.
        inputs (list of :obj:`nnabla.Variable` and None): Input Variables of the forward function
            if this backward function depends on it. Otherwise, None is set instead.
        input_shapes (list of tuple of :obj:`int`): Input shapes of the forward function.
            The shapes of the inputs in which None is set can be passed.
        outputs (list of :obj:`nnabla.Variable` and None): Output Variables of the forward function
            if this backward function depends on it. Otherwise, None is set instead.
        output_shapes (list of tuple of :obj:`int`): Output shapes of the forward function.
            The shapes of the outputs in which None is set can be passed.
        kwargs (dict of arguments): Dictionary of the corresponding function arguments.
  
      Return:
        list of Variable: Return the gradients wrt inputs of the corresponding function.
      """
      if not output_u:
          # We need to get original `u` from output for gradient calculation.
          raise ValueError(
              "spectral_norm_backward is supported for output_u=True."
          )
  
      dw_sn = grad_inputs[0]
      w = inputs[0]
      u = outputs[1]
  
      if dim == w.ndim - 1:
          return _spectral_norm_outer_most_dim_backward(
              dw_sn, w, u, itr, eps
          )
      else:
          return _spectral_norm_backward(dw_sn, w, u, dim, itr, eps)
  
imports: import numpy
  import nnabla
  import nnabla.functions
  from .utils import no_grad, sum_for_arithmetics
label_desc: Use image node_id 3 for calling a global function with example usage: spectral_norm_backward(grad_inputs, inputs, input_shapes, outputs, output_shapes, dim, itr, eps, test, output_u) and returns: _spectral_norm_outer_most_dim_backward, _spectral_norm_backward