[ML] Make warnings from inference errors #81735
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Pinging @elastic/ml-core (Team:ML) |
benwtrent
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You need to update the PyTorchModelIT to make sure that no warnings are written.
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| ActionListener.wrap(this::onSuccess, this::onFailure) | |
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this should probably be expectThrows
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PyTorchModelIT#testPipelineWithBadProcessor Needs to be updated as it expects a |
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💔 Backport failed
You can use sqren/backport to manually backport by running |
davidkyle
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Consistently using exceptions for errors instead of WarningInferenceResults to simplify debugging/triaging # Conflicts: # x-pack/plugin/ml/qa/native-multi-node-tests/src/javaRestTest/java/org/elasticsearch/xpack/ml/integration/PyTorchModelIT.java # x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/inference/nlp/FillMaskProcessor.java # x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/inference/nlp/NerProcessor.java # x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/inference/nlp/FillMaskProcessorTests.java # x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/inference/nlp/NerProcessorTests.java # x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/inference/nlp/TextClassificationProcessorTests.java
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Consistently using exceptions for errors instead of WarningInferenceResults to simplify debugging/triaging # Conflicts: # x-pack/plugin/ml/qa/native-multi-node-tests/src/javaRestTest/java/org/elasticsearch/xpack/ml/integration/PyTorchModelIT.java # x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/inference/nlp/FillMaskProcessor.java # x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/inference/nlp/NerProcessor.java # x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/inference/nlp/FillMaskProcessorTests.java # x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/inference/nlp/NerProcessorTests.java # x-pack/plugin/ml/src/test/java/org/elasticsearch/xpack/ml/inference/nlp/TextClassificationProcessorTests.java
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Consistently using exceptions for errors instead of
WarningInferenceResults. Using a mixture of the 2 complicates debugging and triaging as more both warnings and exceptions have to be checked.Many of the uses of
WarningInferenceResultsrelated to validating the output of the native pytorch process. Those unexpected results are more accurately internal server errors not a warning.Follow up to #81475