[ML] Update the number of allocations per nlp process #86277
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Pinging @elastic/ml-core (Team:ML) |
| TimeValue timeout, | ||
| ActionListener<ThreadSettings> listener | ||
| ) { | ||
| var processContext = getProcessContext(task, listener::onFailure); |
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There seems to be another method which we could extract here that is something like executePyTorchAction and takes in an AbstractPyTorchAction. Then we could reuse it when we fire either the inference action or the control message action and it does the getting of the process context and the try-catch of running the action.
I might be missing something that makes it impossible to do this. In any case, just a thought.
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++ yeah there was an opportunity to refactor here
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During elastic#86277 an error was introduced in parsing of pytorch thread settings. This commit fixes the issue.
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During #86277 an error was introduced in parsing of pytorch thread settings. This commit fixes the issue.
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During elastic#86277 an error was introduced in parsing of pytorch thread settings. This commit fixes the issue.
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This is the Java side of elastic/ml-cpp#2258 which causes internal breakages while the PRs are out of sync due to naming changes.
Adds a method to
DeploymentManagerto update the number of allocations per process as implemented in elastic/ml-cpp#2258.Also
PyTorchResultsnow has an error type rather than the error being a special case of the inference result and reverts the test mutes in #86263