code: def forward(self, x):
      x = self.linear2(self.dropout1(self.activation(self.linear1(x))))
      return self.dropout2(x)
  
imports: import numpy
  import math
  from math import sqrt
  import os
  from scipy.fftpack import next_fast_len
  from merlion.models.utils.nn_modules.blocks import ExponentialSmoothing, conv1d_fft
label_desc: Use image node_id 2 for calling the MLPLayer obj's underlying member method code with example usage: obj.forward(x) and returns: self