code: def __init__(
      self, channels, attention_channels=128, global_context=True
  ):
      super().__init__()
  
      self.eps = 1e-12
      self.global_context = global_context
      if global_context:
          self.tdnn = TDNNBlock(channels * 3, attention_channels, 1, 1)
      else:
          self.tdnn = TDNNBlock(channels, attention_channels, 1, 1)
      self.tanh = nn.Tanh()
      self.conv = Conv1d(
          in_channels=attention_channels,
          out_channels=channels,
          kernel_size=1,
      )
  
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 AttentiveStatisticsPooling object from inherited base classes: nn with example: obj = AttentiveStatisticsPooling(channels, attention_channels, global_context)