docstr: Get the final value of the objective function from the GLRM model.
  
  :returns: final objective value (double).
  
  :examples:
  
  >>> from h2o.estimators import H2OGeneralizedLowRankEstimator
  >>> from h2o.grid.grid_search import H2OGridSearch
  >>> iris = h2o.import_file("http://h2o-public-test-data.s3.amazonaws.com/smalldata/iris/iris_wheader.csv")
  >>> hyper_parameters = {'gamma_x': [0.05, 0.5], 'gamma_y': [0.05,0.5]}
  >>> gs = H2OGridSearch(H2OGeneralizedLowRankEstimator(),
  ...                    hyper_parameters)
  >>> gs.train(x=iris.names, training_frame=iris)
  >>> gs.objective()
docstr_tok: ["Get","the","final","value","of","the","objective","function","from","the","GLRM","model",".",":","returns",":","final","objective","value","(","double",")",".",":","examples",":",">",">",">","from","h2o.estimators","import","H2OGeneralizedLowRankEstimator",">",">",">","from","h2o.grid.grid_search","import","H2OGridSearch",">",">",">","iris","=","h2o.import_file","(","``","http",":","\/\/h2o-public-test-data.s3.amazonaws.com\/smalldata\/iris\/iris_wheader.csv","''",")",">",">",">","hyper_parameters","=","{","'gamma_x","'",":","[","0.05",",","0.5","]",",","'gamma_y","'",":","[","0.05,0.5","]","}",">",">",">","gs","=","H2OGridSearch","(","H2OGeneralizedLowRankEstimator","(",")",",","...","hyper_parameters",")",">",">",">","gs.train","(","x=iris.names",",","training_frame=iris",")",">",">",">","gs.objective","(",")"]
code: def objective(self):
      """
      Get the final value of the objective function from the GLRM model.
  
      :returns: final objective value (double).
  
      :examples:
  
      >>> from h2o.estimators import H2OGeneralizedLowRankEstimator
      >>> from h2o.grid.grid_search import H2OGridSearch
      >>> iris = h2o.import_file("http://h2o-public-test-data.s3.amazonaws.com/smalldata/iris/iris_wheader.csv")
      >>> hyper_parameters = {'gamma_x': [0.05, 0.5], 'gamma_y': [0.05,0.5]}
      >>> gs = H2OGridSearch(H2OGeneralizedLowRankEstimator(),
      ...                    hyper_parameters)
      >>> gs.train(x=iris.names, training_frame=iris)
      >>> gs.objective()
      """
      return {model.model_id: model.objective for model in self.models}
  
label_desc: Use image node_id 2 for calling the H2ODimReductionGridSearch obj's underlying member method code with example usage: obj.objective() and returns: unknown