code: def forward(self, x, lengths=None):
      xl = []
      for layer in self.blocks:
          try:
              x = layer(x, lengths=lengths)
          except TypeError:
              x = layer(x)
          xl.append(x)
  
      # Multi-layer feature aggregation
      x = paddle.concat(xl[1:], axis=1)
      x = self.mfa(x)
  
      # Attentive Statistical Pooling
      x = self.asp(x, lengths=lengths)
      x = self.asp_bn(x)
  
      # Final linear transformation
      x = self.fc(x)
  
      return x
  
imports: import math
  import os
  import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 2 for calling the ECAPA_TDNN obj's underlying member method code with example usage: obj.forward(x, lengths) and returns: x