Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Failing to prune XGBoost tree models #21

Open
xiaoqiao21 opened this issue Jul 1, 2021 · 3 comments
Open

Failing to prune XGBoost tree models #21

xiaoqiao21 opened this issue Jul 1, 2021 · 3 comments

Comments

@xiaoqiao21
Copy link

Hi, I want to use sklearn2pmml() function to convert a PMML file.

I created an issuse below, but I was not able to reopen it so I create this new issue and just copy the content again here.
jpmml/jpmml-sklearn#160

Here is my code to create a pipeline. But I saw an error

RuntimeError: The JPMML-SkLearn conversion application has failed. The Java executable should have printed more information about the failure into its standard output and/or standard error streams

How can I solve it? My version is 0.73.1

The standout is

Standard output is empty
Standard error:
Jul 01, 2021 8:33:28 PM org.jpmml.sklearn.Main run
INFO: Parsing PKL..
Jul 01, 2021 8:33:28 PM org.jpmml.sklearn.Main run
INFO: Parsed PKL in 219 ms.
Jul 01, 2021 8:33:28 PM org.jpmml.sklearn.Main run
INFO: Converting PKL to PMML..
Jul 01, 2021 8:33:30 PM org.jpmml.sklearn.Main run
SEVERE: Failed to convert PKL to PMML
java.lang.IllegalArgumentException
	at org.jpmml.converter.visitors.AbstractTreeModelTransformer.initScore(AbstractTreeModelTransformer.java:173)
	at org.jpmml.converter.visitors.TreeModelPruner.exitNode(TreeModelPruner.java:81)
	at org.jpmml.converter.visitors.AbstractTreeModelTransformer.popParent(AbstractTreeModelTransformer.java:61)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:120)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:90)
	at org.dmg.pmml.tree.TreeModel.accept(TreeModel.java:401)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:90)
	at org.dmg.pmml.mining.Segment.accept(Segment.java:235)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.mining.Segmentation.accept(Segmentation.java:185)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:69)
	at org.dmg.pmml.mining.MiningModel.accept(MiningModel.java:349)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:90)
	at org.dmg.pmml.mining.Segment.accept(Segment.java:235)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.mining.Segmentation.accept(Segmentation.java:185)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:69)
	at org.dmg.pmml.mining.MiningModel.accept(MiningModel.java:349)
	at org.jpmml.model.visitors.AbstractVisitor.applyTo(AbstractVisitor.java:320)
	at org.jpmml.xgboost.Learner.encodeMiningModel(Learner.java:354)
	at xgboost.sklearn.BoosterUtil.encodeBooster(BoosterUtil.java:63)
	at xgboost.sklearn.XGBClassifier.encodeModel(XGBClassifier.java:45)
	at xgboost.sklearn.XGBClassifier.encodeModel(XGBClassifier.java:27)
	at sklearn.Estimator.encode(Estimator.java:83)
	at sklearn2pmml.pipeline.PMMLPipeline.encodePMML(PMMLPipeline.java:235)
	at org.jpmml.sklearn.Main.run(Main.java:226)
	at org.jpmml.sklearn.Main.main(Main.java:143)

Exception in thread "main" java.lang.IllegalArgumentException
	at org.jpmml.converter.visitors.AbstractTreeModelTransformer.initScore(AbstractTreeModelTransformer.java:173)
	at org.jpmml.converter.visitors.TreeModelPruner.exitNode(TreeModelPruner.java:81)
	at org.jpmml.converter.visitors.AbstractTreeModelTransformer.popParent(AbstractTreeModelTransformer.java:61)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:120)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.tree.SimpleNode.accept(SimpleNode.java:113)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:90)
	at org.dmg.pmml.tree.TreeModel.accept(TreeModel.java:401)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:90)
	at org.dmg.pmml.mining.Segment.accept(Segment.java:235)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.mining.Segmentation.accept(Segmentation.java:185)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:69)
	at org.dmg.pmml.mining.MiningModel.accept(MiningModel.java:349)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:90)
	at org.dmg.pmml.mining.Segment.accept(Segment.java:235)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:108)
	at org.dmg.pmml.mining.Segmentation.accept(Segmentation.java:185)
	at org.dmg.pmml.PMMLObject.traverse(PMMLObject.java:69)
	at org.dmg.pmml.mining.MiningModel.accept(MiningModel.java:349)
	at org.jpmml.model.visitors.AbstractVisitor.applyTo(AbstractVisitor.java:320)
	at org.jpmml.xgboost.Learner.encodeMiningModel(Learner.java:354)
	at xgboost.sklearn.BoosterUtil.encodeBooster(BoosterUtil.java:63)
	at xgboost.sklearn.XGBClassifier.encodeModel(XGBClassifier.java:45)
	at xgboost.sklearn.XGBClassifier.encodeModel(XGBClassifier.java:27)
	at sklearn.Estimator.encode(Estimator.java:83)
	at sklearn2pmml.pipeline.PMMLPipeline.encodePMML(PMMLPipeline.java:235)
	at org.jpmml.sklearn.Main.run(Main.java:226)
	at org.jpmml.sklearn.Main.main(Main.java:143)
@vruusmann
Copy link
Member

Looks like you've trained an XGBoost model, which contains no-op nodes.

The JPMML-XGBoost automatically tries to eliminate those nodes (because they are provably unreachable under any and all scenarios) by applying a special tree model pruning algorithm implementes as org.jpmml.converter.visitors.TreeModelPruner.

I was sure that the tree pruning code will always succeed. However, you've managed to train an XGBoost model that contains such an unusual "internal structure" that the tree pruning code still fails.

Can you share your model file so that I could take a look at this unusual "internal structure" myself? Or if it's trained on proprietary data, can you reproduce the pruning error using some publicly available toy dataset?

@vruusmann
Copy link
Member

As a workaround, you should dsable tree pruning by specifying the prune = False conversion option:

pipeline = PMMLPipeline([
  ("xgb", XGBClassifier())
])
pipeline.fit(X, y)
# THIS - specify conversion options right after fitting the pipeline
pipeline.configure(prune = False)

sklearn2pmml(pipeline, "XGBoost.pmml")

@vruusmann vruusmann changed the title Cannot convert to PMML Failure to prune XGBoost tree models Jul 2, 2021
@vruusmann vruusmann changed the title Failure to prune XGBoost tree models Failing to prune XGBoost tree models Jul 2, 2021
@xiaoqiao21
Copy link
Author

Thanks a lot! It works now

@vruusmann vruusmann transferred this issue from jpmml/jpmml-sklearn Aug 22, 2021
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
2 participants
@vruusmann @xiaoqiao21