code: def __init__(
      self, input_c: int, expand_c: int, se_ratio: float = 0.25
  ):
      super(SqueezeExcitation, self).__init__()
      squeeze_c = int(input_c * se_ratio)
      self.fc1 = nn.Conv2d(expand_c, squeeze_c, 1)
      self.ac1 = nn.ReLU(inplace=True)
      self.fc2 = nn.Conv2d(squeeze_c, expand_c, 1)
      self.ac2 = nn.Sigmoid()
  
imports: from typing import Optional
  import numpy
  import torch
  import torch.nn
  from torch import Tensor
label_desc: Use image node_id 1 to create a new SqueezeExcitation object from inherited base classes: nn with example: obj = SqueezeExcitation(input_c, expand_c, se_ratio)