bergamot-translator/.gitignore

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# vim temporary files
*.swp
*.swo
# CMake
CMakeLists.txt.user
CMakeCache.txt
CMakeFiles
CMakeScripts
Testing
Makefile
cmake_install.cmake
install_manifest.txt
compile_commands.json
CTestTestfile.cmake
_deps
wasm/test_page/node_modules
build-wasm
2021-02-15 12:23:08 +03:00
models
wasm/test_page/js/bergamot-translator-worker.*
QualityEstimation: Preliminary Implementation (#197) Unifies quality estimation with an interface, refactors previously available quality scores to fit this interface. Adds a new class of model with Logistic Regression powering the predictions as an implementation of said interface. QE now provides annotations on words using subwords to word rule-based algorithms working with space characters. QualityEstimation ----------------- Implementations of QE are bound together by a `QualityEstimator` Interface. 1. The log-probabilities from the machine-translation model re-interpreted as quality scores are crafted as an implementation of QualityEstimator. 2. A Logistic-Regression based model is added. This class of models is trained supervised with scores labeled by a human annotator. Handcrafted features - number of words, log probs from MT model and statistics over the sequence are used to generate the numeric features. LogisticRegressor, Matrix (to hold features) are added. The creation of an instance is switched by the `AlignedMemory` supplied (be it loaded from the file-system or supplied as a parameter). An empty AlignedMemory leads to quality scores from NMT while supplying weights of a trained logistic-regression model in binary format as the contents lead to an additional pass through the said model to provide more refined scores. Both the above now transform subwords into "words" using a heuristic algorithm, scanning for spaces. This allows the client to work with "words" to denote quality instead of subwords, as the former is more sensible to the user. Testing ------- 1. BRT now has two new test apps to check the QE outputs in text (covers subword to words) and numbers domain (covers quality scores). These are tested with en-et models for which QualityEstimation is available now, on a new input to avoid architecture/compiler issues. 2. Unit test for LogisticRegression model is added. Docs ---- Doxygen now supports MathJax properly to render explanations for Logistic Regressions' reductions in place to make computation more efficient correctly. Co-authored-by: Felipe C. Dos Santos <felipe.santos.k@gmail.com> Co-authored-by: Jerin Philip <jerinphilip@live.in>
2021-09-16 18:28:40 +03:00
# VSCode
.vscode