code: def gaussian_likelihood(input_, mu_, log_std):
      """
      Helper to computer log likelihood of a gaussian.
      Here we assume this is a Diagonal Gaussian.
  
      :param input_: (tf.Tensor)
      :param mu_: (tf.Tensor)
      :param log_std: (tf.Tensor)
      :return: (tf.Tensor)
      """
      pre_sum = -0.5 * (
          ((input_ - mu_) / (tf.exp(log_std) + EPS)) ** 2
          + 2 * log_std
          + np.log(2 * np.pi)
      )
      return tf.reduce_sum(pre_sum, axis=1)
  
imports: import tensorflow
  import numpy
  from gym.spaces import Box
  from stable_baselines.common.policies import BasePolicy, nature_cnn, register_policy
  from stable_baselines.common.tf_layers import mlp
label_desc: Use image node_id 1 for calling a global function with example usage: gaussian_likelihood(input_, mu_, log_std) and returns: tf