code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size,
      dilation,
      activation=nn.ReLU,
  ):
      super(TDNNBlock, self).__init__()
      self.conv = Conv1d(
          in_channels=in_channels,
          out_channels=out_channels,
          kernel_size=kernel_size,
          dilation=dilation,
      )
      self.activation = activation()
      self.norm = BatchNorm1d(input_size=out_channels)
  
imports: import math
  import os
  import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new TDNNBlock object from inherited base classes: nn with example: obj = TDNNBlock(in_channels, out_channels, kernel_size, dilation, activation)