docstr: evaluate the pipeline
  :param input_df:
  :param metrics: subset of ['mean_squared_error', 'r_square', 'sMAPE']
  :param multioutput: string in ['raw_values', 'uniform_average']
          'raw_values' :
              Returns a full set of errors in case of multioutput input.
          'uniform_average' :
              Errors of all outputs are averaged with uniform weight.
  :return:
docstr_tok: ["evaluate","the","pipeline",":","param","input_df",":",":","param","metrics",":","subset","of","[","'mean_squared_error","'",",","'r_square","'",",","'sMAPE","'","]",":","param","multioutput",":","string","in","[","'raw_values","'",",","'uniform_average","'","]","'raw_values","'",":","Returns","a","full","set","of","errors","in","case","of","multioutput","input",".","'uniform_average","'",":","Errors","of","all","outputs","are","averaged","with","uniform","weight",".",":","return",":"]
code: def evaluate(
      self, input_df, metrics=["mse"], multioutput="raw_values"
  ):
      """
      evaluate the pipeline
      :param input_df:
      :param metrics: subset of ['mean_squared_error', 'r_square', 'sMAPE']
      :param multioutput: string in ['raw_values', 'uniform_average']
              'raw_values' :
                  Returns a full set of errors in case of multioutput input.
              'uniform_average' :
                  Errors of all outputs are averaged with uniform weight.
      :return:
      """
      return self.model.evaluate(df=input_df, metric=metrics)
  
file_path: BigDL/python/chronos/src/bigdl/chronos/autots/deprecated/pipeline/time_sequence.py
imports: import os
  import time
  from bigdl.chronos.autots.deprecated.feature.utils import save_config
  from bigdl.chronos.autots.deprecated.pipeline.base import Pipeline
  from bigdl.chronos.autots.deprecated.model.time_sequence import TimeSequenceModel
  from bigdl.chronos.autots.deprecated.pipeline.parameters import DEFAULT_CONFIG_DIR, DEFAULT_PPL_DIR
  from bigdl.chronos.utils import deprecated
label_desc: Use image node_id 5 for calling the TimeSequencePipeline obj's underlying member method code with example usage: obj.evaluate(input_df, metrics, multioutput) and returns: self