text: import torch.nn as nn
  from utils._cdht.dht_func import C_dht
  
  
  class RT_Layer(nn.Module):
      def __init__(self, input_dim, dim, numAngle, numRho):
          super(RT_Layer, self).__init__()
          self.fist_conv = nn.Sequential(
              nn.Conv2d(input_dim, dim, 1),
              nn.BatchNorm2d(dim),
              nn.ReLU()
          )
          self.rt = RT(numAngle=numAngle, numRho=numRho)
          self.convs = nn.Sequential(
              nn.Conv2d(dim, dim, 3, 1, 1),
              nn.BatchNorm2d(dim),
              nn.ReLU(),
              nn.Conv2d(dim, dim, 3, 1, 1),
              nn.BatchNorm2d(dim),
              nn.ReLU()
          )
      def forward(self, x):
          x = self.fist_conv(x)
          x = self.rt(x)
          x = self.convs(x)
          return x
  
  
  class RT(nn.Module):
      def __init__(self, numAngle, numRho):
          super(RT, self).__init__()
          self.line_agg = C_dht(numAngle, numRho)
  
      def forward(self, x):
          accum = self.line_agg(x)
          return accum
  