All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
- Profiler script.
- Performance enhancements by using batch operations in hugging face and torch. All interaction functions now need to support accepting an array of texts. (The encoding function has changed as a result.)
- Corrected bug in how summation is occuring in sort_salience_map() and added unit test.
- Suggested dev_env.yml environment for contributors.
- API update to devices where "mps" is now checked in addition to "cuda".
- Stopwords will be from tx2 init rather than nltk download.
- Bumped package versions.
- Specified package versions in requirements and setup.py.
- Updating example jupyter notebooks to use new versions of packages.
- Datasources in jupyter example notebooks.
- Updated to patched numpy version 1.22.
- Potential issue in calc.frequent_words_in_cluster() where clusters of empty string values would stop computation.
- Wrapper function still expecting pandas series instead of numpy array.
- Missing nltk.download("stopwords").
- Example notebook demonstrating using TX2 with a huggingface model with sequence classification head, rather than a custom torch implementation.
- Pre-commit hooks.
- Add support for huggingface sequence classification head to default interaction functions.
- Code formatting to fix flake8-indicated issues.