text: import numpy as np
  
  from meta_agents.baselines.base import Baseline
  
  
  class ZeroBaseline(Baseline):
      """
      Dummy baseline
      """
  
      def __init__(self):
          super(ZeroBaseline, self).__init__()
  
      def get_param_values(self, **kwargs):
          """
          Returns the parameter values of the baseline object
  
          Returns:
              (None): coefficients of the baseline
  
          """
          return None
  
      def set_param_values(self, value, **kwargs):
          """
          Sets the parameter values of the baseline object
  
          Args:
              value (None): coefficients of the baseline
  
          """
          pass
  
      def fit(self, paths, **kwargs):
          """
          Improves the quality of zeroes output by baseline
  
          Args:
              paths: list of paths
  
          """
          pass
  
      def predict(self, path):
          """
          Produces some zeroes
  
          Args:
              path (dict): dict of lists/numpy array containing trajectory / path information
                  such as "observations", "rewards", ...
  
          Returns:
               (np.ndarray): numpy array of the same length as paths["observations"] specifying the reward baseline
                  
          """
          return np.zeros_like(path["rewards"])