code: def forward(self, x):
      out = self._attention(x)
      if not self.quantized:
          return out * x
      else:
          x_quant = self.mul_a_quantizer(out)
          return x_quant * self.mul_b_quantizer(x)
  
imports: import copy
  from collections import OrderedDict
  from dataclasses import dataclass
  from typing import Optional
  import torch
  import warnings
  from torch import nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the SequentialSqueezeAndExcitationTRT obj's underlying member method code with example usage: obj.forward(x) and returns: unknown, unknown