* 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>
Upgrades the PyTorch, transformers and sentence transformer requirements.
Elasticsearch has upgraded to PyTorch to 2.3.1 in 8.16 and 8.15.2. For
compatibility reasons Eland will refuse to upload to an Elasticsearch cluster
that has is using an earlier version of PyTorch.
I updated the tree serialization format for the new scikit learn versions. I also updated the minimum requirement of scikit learn to 1.3 to ensure compatibility.
Fixes#555
PyTorch models traced in version 1.13 of PyTorch cannot be evaluated in
version 1.9 or earlier. With this upgrade Eland becomes incompatible with
pre 8.7 Elasticsearch and will refuse to upload a model to the cluster.
In this scenario either upgrade Elasticsearch or use an earlier version of Eland.
Shap is incompatible with NumPy 1.24 due to a deprecated usage becoming
an error. There is no fix in Shap yet so an earlier version of NumPy must
be used.
Pandas 2.0 was recently released we will continue to use the latest 1.5 release
to avoid any incompatibilities.
Elasticsearch uses v1.11 of PyTorch. Models created with the latest PyTorch
release (v1.12) are not compatible with v1.11. This pins the PyTorch version
to 1.11 to prevent the incompatibility. The version of the Elasticsearch Python
client is now required to be >= Eland.
All users of Eland for importing NLP models should upgrade.
In preparation for an 8.0 release, this updates PyTorch NLP dependencies
to more recent and latest minor versions. Amongst other things, this
introduces a fix from transformers that is helpful for text embedding
tasks with certain DPR models.
See: https://github.com/huggingface/transformers/issues/13670
Co-authored-by: Seth Michael Larson <seth.larson@elastic.co>
