code: def backward(ctx, grad_output):
      if ctx.p > 0 and ctx.train:
          return grad_output.mul(ctx.noise), None, None, None
      else:
          return grad_output, None, None, None
  
imports: import copy
  import math
  import torch
  import torch.nn
  import torch.nn.functional
  from stanza.models.constituency.positional_encoding import ConcatSinusoidalEncoding
label_desc: Use image node_id 2 for calling the FeatureDropoutFunction obj's underlying member method code with example usage: obj.backward(ctx, grad_output) and returns: grad_output,  None,  None,  None, grad_output,  None,  None,  None