fix xgboost training with greater than 255 feature columns (#2774)

Author: typhoonzero

go/codegen/xgboost/codegen.go

@@ -228,7 +228,7 @@ func deriveFeatureColumnCodeAndFieldDescs(fcs []ir.FeatureColumn, labelFc ir.Fea
 		}
 	}
 
-	featureColumnsCode = strings.Join(fcCodes, ",")
+	featureColumnsCode = strings.Join(fcCodes, ",\n")
 
 	switch c := labelFc.(type) {
 	case *ir.NumericColumn:

go/codegen/xgboost/template_evaluate.go

@@ -46,7 +46,8 @@ feature_column_names = [{{range .FeatureColumnNames}}
 "{{.}}",
 {{end}}]
 
-transform_fn = xgboost_extended.feature_column.ComposedColumnTransformer(feature_column_names, {{.FeatureColumnCode}})
+feature_column_list = [{{.FeatureColumnCode}}]
+transform_fn = xgboost_extended.feature_column.ComposedColumnTransformer(feature_column_names, *feature_column_list)
 
 evaluate(datasource='''{{.DataSource}}''',
          select='''{{.PredSelect}}''',

go/codegen/xgboost/template_explain.go

@@ -42,7 +42,8 @@ feature_column_names = [{{range .FeatureColumnNames}}
 "{{.}}",
 {{end}}]
 
-transform_fn = xgboost_extended.feature_column.ComposedColumnTransformer(feature_column_names, {{.FeatureColumnCode}})
+feature_column_list = [{{.FeatureColumnCode}}]
+transform_fn = xgboost_extended.feature_column.ComposedColumnTransformer(feature_column_names, *feature_column_list)
 
 explain(
     datasource='''{{.DataSource}}''',

go/codegen/xgboost/template_pred.go

@@ -47,7 +47,8 @@ feature_column_names = [{{range .FeatureColumnNames}}
 "{{.}}",
 {{end}}]
 
-transform_fn = xgboost_extended.feature_column.ComposedColumnTransformer(feature_column_names, {{.FeatureColumnCode}})
+feature_column_list = [{{.FeatureColumnCode}}]
+transform_fn = xgboost_extended.feature_column.ComposedColumnTransformer(feature_column_names, *feature_column_list)
 
 pred(datasource='''{{.DataSource}}''',
      select='''{{.PredSelect}}''',

go/codegen/xgboost/template_train.go

@@ -64,7 +64,8 @@ feature_column_names = [{{range .FeatureColumnNames}}
 
 # NOTE: in the current implementation, we are generating a transform_fn from COLUMN clause. 
 # The transform_fn is executed during the process of dumping the original data into DMatrix SVM file.
-transform_fn = xgboost_extended.feature_column.ComposedColumnTransformer(feature_column_names, {{.FeatureColumnCode}})
+feature_column_list = [{{.FeatureColumnCode}}]
+transform_fn = xgboost_extended.feature_column.ComposedColumnTransformer(feature_column_names, *feature_column_list)
 
 train(datasource='''{{.DataSource}}''',
       select='''{{.TrainSelect}}''',