v1.11.1

Improvements

• Improved functionality for score_definition.py and score_execution.py, allowing for more general usage of the score_model_with_cas task
  • Also allowed for model name to be passed into functions instead of requiring model UUID
• Pickle files now loaded with pd.read_pickle() instead of pickle.load() in score code, allowing for more flexibility between python environments

Bugfixes

• Updated pzmm_generate_complete_model_card.ipynb to have better preprocessing function

v1.11.0

Changes

• Added score_definition.py and score_execution.py to allow for score testing within SAS Model Manager
  • Included optional use of CAS Gateway for faster scoring. Only available in environments where Gateway scoring is properly set up.
• Added ability to include data pre-processing function within python score code using the preprocess_function argument.

Bugfixes

• Fixed issue where settings file was improperly imported in some score code files.

v1.10.7

Bugfixes

• Fixed a bug that caused an error when performing SSL verification without a CA bundle specified.

v1.10.6

Improvements

• Refactor tasks.py to utilize sasctl.pzmm functions.
• Add model_info class to better capture model information.

v1.10.5

Buxfixes

• Updated write_json_files.py to allow for better support for prediction models
• Fixed issues relating to model card support.

v1.10.4

Improvements

• Added example Jupyter notebook for OpenAI models.

Buxfixes

• Dropped support for Python 3.6 and Python 3.7, as those are no longer officially supported versions.
• Added dmcas_misc.json template file for model card generation.
• Updated generation of ModelProperties.json to allow for model card generation immediately upon upload.

v1.10.3

Bugfixes

• Updated all examples to use current versions of sasctl functions
• Fixed bug in generate_model_card that threw an error when trying to generate the dmcas_misc.json file

v1.10.2

Improvements

• 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.

Bugfixes

• Allow for score code to impute NaN values in tables that have been loaded into SAS Model Manager.
• Fix issue where target_value was not being properly set during score code generation
• Updated pzmm_generate_requrirements_json.ipynb so the requirements file is generated properly.
• Added missing statistics to dmcas_fitstat.json file.

v1.10.1

Improvements

• Introduced ability to specify the target index of a binary model when creating score code.
  • index can be specified in pzmm.import_model.ImportModel.import_model()
  • Relevant examples updated to include target_index.

Bugfixes

• Reworked write_score_code.py to allow for proper execution of single line scoring.
• Added template files for assess_model_bias.py to allow for proper execution

v1.10.0

Prep for release