class_docstr: A memory efficient, jit-scripted HardSwish activation
code: def symbolic(g, self):
      input = g.op(
          "Add",
          self,
          g.op("Constant", value_t=torch.tensor(3, dtype=torch.float)),
      )
      hardtanh_ = g.op(
          "Clip",
          input,
          g.op("Constant", value_t=torch.tensor(0, dtype=torch.float)),
          g.op("Constant", value_t=torch.tensor(6, dtype=torch.float)),
      )
      hardtanh_ = g.op(
          "Div",
          hardtanh_,
          g.op("Constant", value_t=torch.tensor(6, dtype=torch.float)),
      )
      return g.op("Mul", self, hardtanh_)
  
imports: import torch
  from torch import nn
  from torch.nn import functional
label_desc: Use image node_id 3 for calling the HardSwishJitAutoFn obj's underlying member method code with example usage: obj.symbolic(g, ) and returns: g