text: import numpy as np
  import random
  from collections import namedtuple, deque
  
  import tensorflow as tf
  from tensorflow import keras
  from tensorflow.keras import layers
  
  inputs = keras.Input(shape=(3,), name="lunar_state")
  
  hiddenLayers = layers.Dense(5, activation="relu", name="hidden1")(inputs)
  hiddenLayers = layers.Dense(4, activation="relu", name="hidden2")(hiddenLayers)
  activationLayer = layers.Dense(6, activation="linear", name="activation")(hiddenLayers)
  
  model = keras.models.Model(inputs=inputs, outputs=activationLayer, name="full_model")
  
  for layer in model.layers[1:]:
      layerWeights = layer.get_weights()
      weight = layerWeights[0]
      bias = layerWeights[1]
  
      for i in range(weight.shape[0]):
          for j in range(weight.shape[1]):
              weight[i, j] = ((j - 3) * 2) + pow((i - 1) * 1.2, 3)
  
      for i in range(bias.shape[0]):
          bias[i] = 2 - i
  
      layer.set_weights(layerWeights)
  
  input = np.vstack([np.array([1, 2, 3]), np.array([-2,4,-6])])
  
  output = model(input).numpy()
  
  a = 5