class_docstr: the network for generating non-deterministic (Gaussian distributed) action from the state input 
class_docstr_tok: ["the","network","for","generating","non-deterministic","(","Gaussian","distributed",")","action","from","the","state","input"]
code: def forward(self, state):
      x = self.linear1(state)
      x = self.linear2(x)
      x = self.linear3(x)
      output = tf.nn.tanh(
          self.output_linear(x)
      )  # unit range output [-1, 1]
      return output
  
imports: import argparse
  import os
  import random
  import time
  import gym
  import matplotlib.pyplot
  import numpy
  import tensorflow
  import tensorflow_probability
  import tensorlayer
  from tensorlayer.layers import Dense
  from tensorlayer.models import Model
label_desc: Use image node_id 2 for calling the PolicyNetwork obj's underlying member method code with example usage: obj.forward(state) and returns: output