implement copilot review, fix failling tests

Author: maurever

h2o-algos/src/main/java/hex/glm/GLM.java

@@ -3416,7 +3416,6 @@ private void scoreAndUpdateModel() {
           _model._useRemoveOffsetEffects = false;
         }
       }
-      _model.generateSummary(_parms._train, _state._iter);
       _lastScore = System.currentTimeMillis();
       long scoringTime = System.currentTimeMillis() - t1;
       _scoringInterval = Math.max(_scoringInterval, 20 * scoringTime); // at most 5% overhead for scoring
@@ -3572,14 +3571,16 @@ private void scorePostProcessing(Frame train, long t1) {
       Log.info(LogMsg("Training metrics computed in " + (t2 - t1) + "ms"));
       if (_valid != null) {
         Frame valid = DKV.<Frame>getGet(_parms._valid);
+        ScoreKeeper validScore = new ScoreKeeper(Double.NaN);
         _model.score(_parms.valid(), null, CFuncRef.from(_parms._custom_metric_func)).delete();
         if(_model._parms._control_variables != null || _model._parms._remove_offset_effects){
           _model._output._validation_metrics_unrestricted_model = ModelMetrics.getFromDKV(_model, valid);
+          validScore.fillFrom(_model._output._validation_metrics_unrestricted_model);
         } else {
           _model._output._validation_metrics = ModelMetrics.getFromDKV(_model, valid); //updated by model.scoreAndUpdateModel
+          validScore.fillFrom(_model._output._validation_metrics);
         }
-        ScoreKeeper validScore = new ScoreKeeper(Double.NaN);
-        validScore.fillFrom(_model._output._validation_metrics);
+
       }
       if(_model._parms._control_variables != null || _model._parms._remove_offset_effects) {
         _model.addUnrestrictedModelScoringInfo(_parms, nclasses(), t2, _state._iter);

h2o-algos/src/test/java/hex/glm/GLMControlVariablesTest.java

@@ -416,11 +416,11 @@ public void testControlVariableMultinomial() {
         GLMModel glm = null;
         try {
             Scope.enter();
-
             Vec cat1 = Vec.makeVec(new long[]{1,1,1,0,0},new String[]{"black","red"},Vec.newKey());
             Vec cat2 = Vec.makeVec(new long[]{1,1,1,0,0},new String[]{"a","b"},Vec.newKey());
             Vec res = Vec.makeVec(new double[]{1,1,2,0,0},cat1.group().addVec());
             train = new Frame(Key.<Frame>make("train"),new String[]{"x1", "x2", "y"},new Vec[]{cat1, cat2,res});
+            DKV.put(train);
 
             GLMModel.GLMParameters params = new GLMModel.GLMParameters();
             params._train = train._key;

h2o-bindings/bin/custom/R/gen_glm.py

@@ -82,7 +82,7 @@ def update_param(name, param):
 h2o.make_unrestricted_glm_model <- function(model, destination_key = NULL, control_variables_enabled = FALSE, remove_offset_effects_enabled = FALSE) {
   stopifnot("GLM wasn't trained with control variables or with remove offset effects." = 
     !is.null(model@params$actual[["control_variables"]]) || isTRUE(model@params$actual[["remove_offset_effects"]]))
-  if ((is.null(model@params$actual[["control_variables"]]) || isTRUE(model@params$actual[["remove_offset_effects"]])) 
+  if ((is.null(model@params$actual[["control_variables"]]) || isFALSE(model@params$actual[["remove_offset_effects"]])) 
       && (isTRUE(control_variables_enabled) || isTRUE(remove_offset_effects_enabled))) { 
        stop("GLM wasn't trained with both control variables and with remove offset effects feature set, the control_variables_enabled and remove_offset_effects_enabled features cannot be used.")  
   }

h2o-py/tests/testdir_algos/glm/pyunit_remove_offset_effects.py

@@ -11,7 +11,7 @@ def glm_remove_offset_effects():
     cars = cars[cars["economy_20mpg"].isna() == 0]
     cars["name"] = cars["name"].asfactor()
     cars["economy_20mpg"] = cars["economy_20mpg"].asfactor()
-    offset = h2o.H2OFrame([[.5]]*cars.nrow)
+    offset = h2o.H2OFrame([[.5]] * cars.nrows)
     offset.set_names(["offset"])
     cars = cars.cbind(offset)
 

h2o-r/h2o-package/R/glm.R

@@ -845,7 +845,7 @@ h2o.makeGLMModel <- function(model,beta) {
 h2o.make_unrestricted_glm_model <- function(model, destination_key = NULL, control_variables_enabled = FALSE, remove_offset_effects_enabled = FALSE) {
   stopifnot("GLM wasn't trained with control variables or with remove offset effects." = 
     !is.null(model@params$actual[["control_variables"]]) || isTRUE(model@params$actual[["remove_offset_effects"]]))
-  if ((is.null(model@params$actual[["control_variables"]]) || isTRUE(model@params$actual[["remove_offset_effects"]])) 
+  if ((is.null(model@params$actual[["control_variables"]]) || isFALSE(model@params$actual[["remove_offset_effects"]])) 
       && (isTRUE(control_variables_enabled) || isTRUE(remove_offset_effects_enabled))) { 
        stop("GLM wasn't trained with both control variables and with remove offset effects feature set, the control_variables_enabled and remove_offset_effects_enabled features cannot be used.")  
   }

h2o-r/tests/testdir_algos/glm/runit_GLM_make_unrestricted_model.R

@@ -63,4 +63,4 @@ glm_make_unrestricted_model_test <- function() {
     assertError(h2o.make_unrestricted_glm_model(prostate_glm_2, control_variables_enabled=TRUE))
 }
 
-doTest("GLM: Remove offset effects works with explain", glm_make_unrestricted_model_test)
+doTest("GLM: Test make unrestricted model", glm_make_unrestricted_model_test)