docstr: Evaluate the model on a list of metrics.
  :param input_df: The input time series data frame, Example:
   datetime   value   "extra feature 1"   "extra feature 2"
   2019-01-01 1.9 1   2
   2019-01-02 2.3 0   2
  :param metric: A list of Strings Available string values are "mean_squared_error",
                "r_square".
  :return: a list of metric evaluation results.
docstr_tok: ["Evaluate","the","model","on","a","list","of","metrics",".",":","param","input_df",":","The","input","time","series","data","frame",",","Example",":","datetime","value","``","extra","feature","1","''","``","extra","feature","2","''","2019-01-01","1.9","1","2","2019-01-02","2.3","0","2",":","param","metric",":","A","list","of","Strings","Available","string","values","are","``","mean_squared_error","''",",","``","r_square","''",".",":","return",":","a","list","of","metric","evaluation","results","."]
code: def evaluate(self, input_df, metric=None):
      """
      Evaluate the model on a list of metrics.
      :param input_df: The input time series data frame, Example:
       datetime   value   "extra feature 1"   "extra feature 2"
       2019-01-01 1.9 1   2
       2019-01-02 2.3 0   2
      :param metric: A list of Strings Available string values are "mean_squared_error",
                    "r_square".
      :return: a list of metric evaluation results.
      """
      Evaluator.check_metric(metric)
      return self.pipeline.evaluate(input_df, metric)
  
file_path: analytics-zoo/pyzoo/zoo/chronos/autots/deprecated/regression/base_predictor.py
imports: import pandas
  import os
  from abc import abstractmethod
  from zoo.orca.automl.metrics import Evaluator
  from zoo.chronos.autots.deprecated.pipeline.time_sequence import TimeSequencePipeline
  from zoo.orca.automl.search.utils import process
  from zoo.chronos.autots.deprecated.config.recipe import *
  from zoo.ray import RayContext
  from zoo.orca.automl.auto_estimator import AutoEstimator
label_desc: Use image node_id 6 for calling the BasePredictor obj's underlying member method code with example usage: obj.evaluate(input_df, metric) and returns: self