Taras Matyashovskyy created SPARK-17048: -------------------------------------------
Summary: ML model read for custom transformers in a pipeline does not work Key: SPARK-17048 URL: https://issues.apache.org/jira/browse/SPARK-17048 Project: Spark Issue Type: Bug Components: ML Affects Versions: 2.0.0 Environment: Spark 2.0.0 Java API Reporter: Taras Matyashovskyy 0. Use Java API :( 1. Create any custom ML transformer 2. Make it MLReadable and MLWritable 3. Add to pipeline 4. Evaluate model, e.g. CrossValidationModel, and save results to disk 5. For custom transformer you can DefaultParamsReader and DefaultParamsWriter, for instance 6. Load model from saved directory 7. All out-of-the-box objects are loaded successfully, e.g. Pipeline, Evaluator, etc. 8. Your custom transformer will fail with NPE Reason: ReadWrite.scala:447 cls.getMethod("read").invoke(null).asInstanceOf[MLReader[T]].load(path) In Java this only works for static methods. As we are implementing MLReadable or MLWritable, then this call should be instance method call. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org