* normalized expected scores if min is < 0
* only normalize scores for ES after 8.19+ / 9.1+
* add 9.1.0 snapshot to build matrix
* get min score from booster trees
* removing typing on function definition
* properly flatten our tree leaf scores
* simplify getting min score
* debugging messages
* get all the matches in better way
* Fix model score normalization.
* lint
* lint again
* lint; correct return for bounds map/list
* revert to Aurelian's fix
* re-lint :/
---------
Co-authored-by: Aurelien FOUCRET <aurelien.foucret@elastic.co>
* Fix test setup to match pandas 2.0 demands
* Use the now deprecated _append method
(Better solution might exist)
* Deal with numeric_only being removed in metrics test
* Skip mad metric for other pandas versions
* Account for differences between pandas versions in describe methods
* Run black
* Check Pandas version first
* Mirror behaviour of installed Pandas version when running value_counts
* Allow passing arguments to the individual asserters
* Fix for method _construct_axes_from_arguments no longer existing
* Skip mad metric if it does not exist
* Account for pandas 2.0 timestamp default behaviour
* Deal with empty vs other inferred data types
* Account for default datetime precision change
* Run Black
* Solution for differences in inferred_type only
* Fix csv and json issues
* Skip two doctests
* Passing a set as indexer is no longer allowed
* Don't validate output where it differs between Pandas versions in the environment
* Update test matrix and packaging metadata
* Update version of Python in the docs
* Update Python version in demo notebook
* Match noxfile
* Symmetry
* Fix trailing comma in JSON
* Revert some changes in setup.py to fix building the documentation
* Revert "Revert some changes in setup.py to fix building the documentation"
This reverts commit ea9879753129d8d8390b3cbbce57155a8b4fb346.
* Use PANDAS_VERSION from eland.common
* Still skip the doctest, but make the output pandas 2 instead of 1
* Still skip doctest, but switch to pandas 2 output
* Prepare for pandas 3
* Reference the right column
* Ignore output in tests but switch to pandas 2 output
* Add line comment about NBVAL_IGNORE_OUTPUT
* Restore missing line and add stderr cell
* Use non-private method instead
* Fix indentation and parameter issues
* If index is not specified, and pandas 1 is present, set it to True
From pandas 2 and upwards, index is set to None by default
* Run black
* Newer version of black might have different opinions?
* Add line comment
* Remove unused import
* Add reason for ignore statement
* Add reason for skip
---------
Co-authored-by: Quentin Pradet <quentin.pradet@elastic.co>
* Fix Docker image build on Linux
* Build Docker images in CI
* Fix bash syntax
* Only load, not push
* Parallelize docker build
It's currently the slowest step.
* Only build Linux images
This PR adds an ability to estimate per deployment and per allocation memory usage of NLP transformer models. It uses torch.profiler and performs logs the peak memory usage during the inference.
This information is then used in Elasticsearch to provision models with sufficient memory (elastic/elasticsearch#98874).
Co-authored-by: David Olaru <dolaru@elastic.co>
* Reduce Docker image size from 4.8GB to 2.2GB
* Use torch+cpu variant if target platform is linux/amd64
Avoids downloading large & unnecessary NVIDIA deps defined in the package on PyPI
* Build linux/arm64 image using buildx and QEMU
