code: def __init__(self, in_channels, squeeze, activation):
      super(SqueezeAndExcitationTRT, self).__init__()
      self.pooling = nn.AdaptiveAvgPool2d(1)
      self.squeeze = nn.Conv2d(in_channels, squeeze, 1)
      self.expand = nn.Conv2d(squeeze, in_channels, 1)
      self.activation = activation
      self.sigmoid = nn.Sigmoid()
  
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 1 to create a new SqueezeAndExcitationTRT object from inherited base classes: nn with example: obj = SqueezeAndExcitationTRT(in_channels, squeeze, activation)