code: def glrm_subset():
      acs_orig = h2o.upload_file(
          path=pyunit_utils.locate(
              "bigdata/laptop/airlines_all.05p.csv"
          )
      )
  
      seeds = [
          2297378124,
          3849570216,
          6733652048,
          8915337442,
          8344418400,
          9416580152,
          2598632624,
          4977008454,
          8273228579,
          8185554539,
          3219125000,
          2998879373,
          7707012513,
          5786923379,
          5029788935,
          935945790,
          7092607078,
          9305834745,
          6173975590,
          5397294255,
      ]
      run_time_ms = []
      iterations = []
      objective = []
      num_runs = 1  # number of times to repeat experiments
  
      for ind in range(num_runs):
          acs_model = H2OGeneralizedLowRankEstimator(
              k=10,
              transform="STANDARDIZE",
              loss="Quadratic",
              multi_loss="Categorical",
              model_id="clients_core_glrm",
              regularization_x="L2",
              regularization_y="L1",
              gamma_x=0.2,
              gamma_y=0.5,
              init="SVD",
              max_iterations=200,
              seed=seeds[ind % len(seeds)],
          )
          acs_model.train(
              x=acs_orig.names,
              training_frame=acs_orig,
              seed=seeds[ind % len(seeds)],
          )
          run_time_ms.append(
              acs_model._model_json["output"]["end_time"]
              - acs_model._model_json["output"]["start_time"]
          )
          iterations.append(
              acs_model._model_json["output"]["iterations"]
          )
          objective.append(acs_model._model_json["output"]["objective"])
  
      print("Run time in ms: {0}".format(run_time_ms))
      print("number of iterations: {0}".format(iterations))
      print("objective function value: {0}".format(objective))
      sys.stdout.flush()
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.glrm import H2OGeneralizedLowRankEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: glrm_subset() without return types