code: def __init__(self, name):
      super(MLP, self).__init__(name=name)
      self.h1 = tl.layers.Dense(
          64,
          tf.nn.tanh,
          in_channels=in_dim[0],
          W_init=tf.initializers.GlorotUniform(),
      )
      self.qvalue = tl.layers.Dense(
          out_dim * atom_num,
          in_channels=64,
          name="q",
          W_init=tf.initializers.GlorotUniform(),
      )
      self.reshape = tl.layers.Reshape((-1, out_dim, atom_num))
  
imports: import argparse
  import os
  import random
  import time
  import gym
  import matplotlib.pyplot
  import numpy
  import tensorflow
  import tensorlayer
label_desc: Use image node_id 1 to create a new MLP object from inherited base classes: tl.models with example: obj = MLP(name)