code: def partial_plot_test_with_no_user_splits_no_1DPDP():
      data = h2o.import_file(
          pyunit_utils.locate("smalldata/prostate/prostate_cat_NA.csv")
      )
      x = data.names
      y = "CAPSULE"
      x.remove(y)
  
      # Build a GBM model predicting for response CAPSULE
      gbm_model = H2OGradientBoostingEstimator(
          ntrees=50, learn_rate=0.05, seed=12345
      )
      gbm_model.train(x=x, y=y, training_frame=data)
  
      # pdp without weight or NA
      pdp2dOnly = gbm_model.partial_plot(
          frame=data,
          server=True,
          plot=False,
          col_pairs_2dpdp=[["AGE", "PSA"], ["AGE", "RACE"]],
      )
      pdp1D2D = gbm_model.partial_plot(
          frame=data,
          cols=["AGE", "RACE", "DCAPS"],
          server=True,
          plot=False,
          col_pairs_2dpdp=[["AGE", "PSA"], ["AGE", "RACE"]],
      )
      # compare results 2D pdp
      pyunit_utils.assert_H2OTwoDimTable_equal_upto(
          pdp2dOnly[0],
          pdp1D2D[3],
          pdp2dOnly[0].col_header,
          tolerance=1e-10,
      )
      pyunit_utils.assert_H2OTwoDimTable_equal_upto(
          pdp2dOnly[1],
          pdp1D2D[4],
          pdp2dOnly[1].col_header,
          tolerance=1e-10,
      )
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators import H2OGradientBoostingEstimator
  import os
label_desc: Use image node_id 1 for calling a global function with example usage: partial_plot_test_with_no_user_splits_no_1DPDP() without return types