text: import torch.nn as nn
  
  class FCBaseModel(nn.Module):
      def __int__(self, input_frames=7, n_features=257):
          super(FCBaseModel, self).__int__()
          self.main = nn.Sequential(
              nn.Linear(n_features * input_frames, 2048),
              nn.Sigmoid(),
              nn.Linear(2048, 2048),
              nn.Sigmoid(),
              nn.Linear(2048, 2048),
              nn.Sigmoid(),
              nn.Linear(2048, n_features),
          )
  
      def forward(self, ipt):
          return self.main(ipt)
  
  
  class FCLayerWithMultipleFrames(nn.Module):
      """
      构建多帧 LPS 作为输入的全连接网络层
      """
  
      def __init__(self, input_frames=7, n_features=257):
          """
          初始化全连接层，以多帧 LPS 作为输入
          Args:
              input_frames: 输入的 LPS 特征帧数
              n_features: LPS 特征的维度
          """
          super(FCLayerWithMultipleFrames, self).__init__()
          self.main = nn.Sequential(
              nn.Linear(n_features * input_frames, 2048),
              nn.Sigmoid(),
              nn.Linear(2048, n_features)
          )
  
  
      def forward(self, ipt):
          return self.main(ipt)
  
  
  class FCLayerWithSingleFrame(nn.Module):
      def __init__(self, n_features=257):
          """
          初始化全连接层，以单帧 LPS 作为输入
          Args:
              n_features: LPS 特征的维度
          """
          super(FCLayerWithSingleFrame, self).__init__()
          self.main = nn.Sequential(
              nn.Linear(n_features, 2048),
              nn.Sigmoid(),
              nn.Linear(2048, n_features),
          )
  
  
      def forward(self, ipt):
          return self.main(ipt)
  