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[ML] Update trained model inference endpoint #556
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README.md
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[API](https://www.elastic.co/guide/en/elasticsearch/reference/current/start-trained-model-deployment.html) | ||
you will be able to set the threading options to make best use of your | ||
[API](https://www.elastic.co/guide/en/elasticsearch/reference/current/infer-trained-model.html) | ||
you will be able to set the threading options to make the best use of your |
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This change isn't necessary. The start trained model deployment API still exists, and is the one where threading options are set.
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self.quantize = ( | ||
True | ||
if not (platform.system() == "Darwin" and platform.machine() == "arm64") |
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The changes in this file should go in a separate PR. It will be hard to search for them in the future if they're in a PR that's about updating the model inference endpoint.
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Thanks for fixing the test
README.md
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@@ -244,8 +244,8 @@ command line and instead start the model using the ML UI in Kibana. | |||
The `--start` argument will deploy the model with one allocation and one | |||
thread per allocation, which will not offer good performance. When starting | |||
the model deployment using the ML UI in Kibana or the Elasticsearch | |||
[API](https://www.elastic.co/guide/en/elasticsearch/reference/current/start-trained-model-deployment.html) | |||
you will be able to set the threading options to make best use of your | |||
[API](https://www.elastic.co/guide/en/elasticsearch/reference/current/infer-trained-model.html) |
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[API](https://www.elastic.co/guide/en/elasticsearch/reference/current/infer-trained-model.html) | |
[API](https://www.elastic.co/guide/en/elasticsearch/reference/current/start-trained-model-deployment.html) |
This is referring to the start API
("n_node_samples", "<i8"), | ||
("weighted_n_node_samples", "<f8"), | ||
], | ||
dtype={ |
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We should update the scikit learn version in requirements-dev.txt
and setup.py
otherwise these tests will fail for anyone on an older version
Currently it is:
scikit-learn>=0.22.1,<2
Suggest:
scikit-learn>=1.3,<2
Thank you for your comments. I moved the fix of unit tests into #558. Once merged, the changes here should be related to the deprecated API only. |
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LGTM
Infer trained model deployment API has been deprecated, so I changed the code to use the new one.