[ML] Make warnings from inference errors #81735
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Pinging @elastic/ml-core (Team:ML) |
benwtrent
reviewed
Dec 14, 2021
| @@ -371,32 +369,17 @@ protected void doRun() throws Exception { | |||
| processContext, | |||
| request.tokenization, | |||
| processor.getResultProcessor((NlpConfig) config), | |||
| ActionListener.wrap(this::onSuccess, f -> handleFailure(f, this)) | |||
| ActionListener.wrap(this::onSuccess, this::onFailure) | |||
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| ActionListener.wrap(this::onSuccess, this::onFailure) | |
| this |
| @@ -92,7 +91,7 @@ public void testProcessResults_GivenMissingTokens() { | |||
| PyTorchResult pyTorchResult = new PyTorchResult("1", new double[][][] { { {} } }, 0L, null); | |||
| assertThat( | |||
| FillMaskProcessor.processResult(tokenization, pyTorchResult, tokenizer, 5, randomAlphaOfLength(10)), | |||
| instanceOf(WarningInferenceResults.class) | |||
| instanceOf(ElasticsearchStatusException.class) | |||
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this should probably be expectThrows
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PyTorchModelIT#testPipelineWithBadProcessor Needs to be updated as it expects a |
benwtrent
approved these changes
Dec 14, 2021
💔 Backport failed
You can use sqren/backport to manually backport by running |
davidkyle
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Dec 15, 2021
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
elasticsearchmachine
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Dec 15, 2021
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