code: def backward(ctx, grad_output):
      input_or_output, mean, invvar = ctx.saved_tensors
      grad_input = fused_layer_norm_cuda.backward(
          grad_output.contiguous(),
          mean,
          invvar,
          input_or_output,
          ctx.normalized_shape,
          ctx.eps,
          ctx.memory_efficient,
      )
      return grad_input, None, None, None
  
imports: import importlib
  import numbers
  import torch
  from torch.nn.parameter import Parameter
  from torch.nn import init
  from torch.nn import functional
  from apex._autocast_utils import _cast_if_autocast_enabled
label_desc: Use image node_id 2 for calling the FusedLayerNormFunction obj's underlying member method code with example usage: obj.backward(ctx, grad_output) and returns: grad_input,  None,  None,  None