Recent Releases of TX$^2$
TX$^2$ - v1.2.1
Added
- Profiler script.
Changed
- 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.)
Fixed
- Corrected bug in how summation is occuring in sortsaliencemap() and added unit test.
Scientific Software - Peer-reviewed
- Python
Published by WarmCyan over 3 years ago
TX$^2$ - v1.1.0
Added
- Suggested dev_env.yml environment for contributors.
- API update to devices where "mps" is now checked in addition to "cuda".
Changed
- 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.
Fixed
- Updated to patched numpy version 1.22.
- Potential issue in calc.frequentwordsin_cluster() where clusters of empty string values would stop computation.
Scientific Software - Peer-reviewed
- Python
Published by WarmCyan over 3 years ago
TX$^2$ - v1.0.1
Added
- Example notebook demonstrating using TX2 with a huggingface model with sequence classification head, rather than a custom torch implementation.
- Pre-commit hooks.
Changed
- Add support for huggingface sequence classification head to default interaction functions.
Fixed
- Code formatting to fix flake8-indicated issues.
Scientific Software - Peer-reviewed
- Python
Published by WarmCyan almost 4 years ago
TX$^2$ - v1.0.0
We're considering this library's API relatively stable at this point, so we're making this our 1.0 release and will be following semver for any future updates!
Notable changes from pre-1.0 version:
* The wrapper class now takes numpy arrays and/or pandas series rather than dataframes and column names for the training and testing data. (See the wrapper docs and the second code block in basic usage#default-approach for an example)
* We have unit tests now! They can be run with pytest from the project root
* The cuda torch device can be overridden for the default encoding handler, this is passed to the wrapper constructor with cuda_device
* Version specifications are added for several of the required dependencies
* Many various bug fixes
Scientific Software - Peer-reviewed
- Python
Published by WarmCyan about 4 years ago