code: def backward(ctx, grad_output):
      x = ctx.saved_tensors[0]
      sx = torch.sigmoid(x)
      fx = F.softplus(x).tanh()
      return grad_output * (fx + x * sx * (1 - fx * fx))
  
imports: import torch.nn.functional
  from .utils import *
label_desc: Use image node_id 2 for calling the MishImplementation obj's underlying member method code with example usage: obj.backward(ctx, grad_output) and returns: unknown