code: def __init__(
      self,
      inplanes,
      squeeze_planes,
      expand1x1_planes,
      expand3x3_planes,
      dilation=1,
  ):
      super(Fire, self).__init__()
      self.inplanes = inplanes
      self.squeeze = nn.Conv2d(inplanes, squeeze_planes, kernel_size=1)
      self.squeeze_activation = nn.ReLU(inplace=True)
      self.expand1x1 = nn.Conv2d(
          squeeze_planes, expand1x1_planes, kernel_size=1
      )
      self.expand1x1_activation = nn.ReLU(inplace=True)
      self.expand3x3 = nn.Conv2d(
          squeeze_planes,
          expand3x3_planes,
          kernel_size=3,
          padding=dilation,
          dilation=dilation,
      )
      self.expand3x3_activation = nn.ReLU(inplace=True)
  
imports: from collections import OrderedDict
  import math
  import re
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils import model_zoo
  from torchvision.models.densenet import DenseNet
  from torchvision.models.squeezenet import squeezenet1_1
label_desc: Use image node_id 1 to create a new Fire object from inherited base classes: nn with example: obj = Fire(inplanes, squeeze_planes, expand1x1_planes, expand3x3_planes, dilation)