code: def forward(self, x):
      h = F.tanh(self.linear(x))
      mu = self.mu(h)
      ln_sigma = self.ln_sigma(h)  # log(sigma)
      return D.Independent(D.Normal(loc=mu, log_scale=ln_sigma))
  
imports: import numpy
  import chainer
  import chainer.distributions
  import chainer.functions
  import chainer.links
  from chainer import reporter
label_desc: Use image node_id 2 for calling the Encoder obj's underlying member method code with example usage: obj.forward(x) and returns: D