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release: v1.10.7
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CHANGELOG.md

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v1.10.7 (2024-10-02)
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--------------------
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**Bugfixes**
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- Fixed a bug that caused an error when performing SSL verification without a CA bundle specified.
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v1.10.6 (2024-08-26)
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**Improvements**
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- Refactor `tasks.py` to utilize `sasctl.pzmm` functions.
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- Add `model_info` class to better capture model information.
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v1.10.5 (2024-08-01)
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**Buxfixes**
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- Updated `write_json_files.py` to allow for better support for prediction models
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- Fixed issues relating to model card support.
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v1.10.4 (2024-07-08)
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**Improvements**
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- Added example Jupyter notebook for OpenAI models.
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- Updated generation of `ModelProperties.json` to allow for model card generation immediately upon upload.
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v1.10.3 (2024-04-12)
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**Bugfixes**
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- Updated all examples to use current versions of sasctl functions
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- Fixed bug in `generate_model_card` that threw an error when trying to generate the `dmcas_misc.json` file
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v1.10.2 (2024-04-10)
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**Improvements**
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- Introduced `generate_model_card` into `write_json_files.py` to allow for python models to work with planned model card tab in SAS Model Manager.
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- Added missing statistics to `dmcas_fitstat.json` file.
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v1.10.1 (2023-08-24)
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**Improvements**
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- Introduced ability to specify the target index of a binary model when creating score code.
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- index can be specified in `pzmm.import_model.ImportModel.import_model()`
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- Added template files for `assess_model_bias.py` to allow for proper execution
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v1.10 (2023-08-31)
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------------------
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**Improvements**
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- `write_score_code.py` refactored to include ability to run batch scoring.
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- Added handling for TensorFlow Keras models.
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- Updated `pzmm_custom_kpi_model_parameters` notebook to have correct parameter casing.
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v1.9.4 (2023-06-15)
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-------------------
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**Improvements**
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- Created pytest fixture to begin running Jupyter notebooks within the GitHub automated test actions.
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- Updated examples:
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- Fixed call to `pzmm.JSONFiles.calculate_model_statistics()` in `pzmm_binary_classification_model_import.ipynb`.
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v1.9.3 (2023-06-08)
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-------------------
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**Improvements**
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- Refactored gitIntegration.py to `git_integration.py` and added unit tests for better test coverage.
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- Fixed issue with `services.model_publish.list_models`, which was using an older API format that is not valid in SAS Viya 3.5 or SAS Viya 4.
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v1.9.2 (2023-05-17)
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**Improvements**
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- Add recursive folder creation and an example.
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- Add example for migrating models from SAS Viya 3.5 to SAS Viya 4.
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- Fix minor errors in h2o score code generation
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v1.9.1 (2023-05-04)
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**Improvements**
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- Updated handling of H2O models in `sasctl.pzmm`.
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- Models are now saved with the appropriate `h2o` functions within the `sasctl.pzmm.PickleModel.pickle_trained_model` function.
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- Added NpEncoder class to check for numpy values in JSON files. Numpy-types cannot be used in SAS Viya.
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v1.9.0 (2023-04-04)
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**Improvements**
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- `sasctl.pzmm` refactored to follow PEP8 standards, include type hinting, and major expansion of code coverage.
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- `sasctl.pzmm` functions that can generate files can now run in-memory instead of writing to disk.
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- Better handling for invalid project versions included.
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v1.8.1 (2023-01-19)
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**Changes**
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- Adjusted workflow for code coverage reporting. Prepped to add components in next release.
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- Added `generate_requirements_json.ipynb` example.

src/sasctl/__init__.py

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# Copyright © 2019, SAS Institute Inc., Cary, NC, USA. All Rights Reserved.
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# SPDX-License-Identifier: Apache-2.0
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__version__ = "1.10.6"
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__version__ = "1.10.7"
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__author__ = "SAS"
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__credits__ = [
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"Yi Jian Ching",

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