Metadata-Version: 2.1
Name: ortografix
Version: 0.3.4
Summary: Seq2seq model with attention for automatic orthographic simplification
Home-page: https://github.com/akb89/ortografix
Author:  Alexandre Kabbach
Author-email: akb@3azouz.net
License: MIT
Download-URL: https://github.com/akb89/ortografix
Description: # ortografix
        [![GitHub release][release-image]][release-url]
        [![PyPI release][pypi-image]][pypi-url]
        [![Build][build-image]][build-url]
        [![MIT License][license-image]][license-url]
        
        
        [release-image]:https://img.shields.io/github/release/akb89/ortografix.svg?style=flat-square
        [release-url]:https://github.com/akb89/ortografix/releases/latest
        [pypi-image]:https://img.shields.io/pypi/v/ortografix.svg?style=flat-square
        [pypi-url]:https://pypi.org/project/ortografix/
        [build-image]:https://img.shields.io/github/workflow/status/akb89/ortografix/CI?style=flat-square
        [build-url]:https://github.com/akb89/ortografix/actions?query=workflow%3ACI
        [license-image]:http://img.shields.io/badge/license-MIT-000000.svg?style=flat-square
        [license-url]:LICENSE.txt
        
        Welcome to ortografix, a seq2seq model for automatic ortografic simplification, coded with pytorch 1.4.
        
        ## Install
        via pip:
        ```shell
        pip3 install ortografix
        ```
        or, after a git clone:
        ```shell
        python3 setup.py install
        ```
        
        ## Train
        To train a model, run:
        ```shell
        ortografix train \
        --data /abs/path/to/training/data \
        --model-type gru \
        --shuffle \
        --hidden-size 256 \
        --num-layers 1 \
        --bias \
        --dropout 0 \
        --learning-rate 0.01 \
        --epochs 10 \
        --print-every 100 \
        --use-teacher-forcing \
        --teacher-forcing-ratio 0.5 \
        --output-dirpath /abs/path/to/output/directory/whereto/save/model \
        --with-attention \
        --character-based
        ```
        
        ## Test
        ### Qualitative evaluation
        To qualitatively evaluate the output of the model on a set of 10 randomly selected sentences from a given dev/test set, run:
        ```shell
        ortografix evaluate \
        --data /abs/path/to/test/data.txt \
        --model /abs/path/to/model/directory/ \
        --random 10
        ```
        ### Quantitative evaluation
        To quantitatively evaluate the output of the model on a given dev/test set, run:
        ```shell
        ortografix evaluate \
        --data /abs/path/to/test/data.txt \
        --model /abs/path/to/model/directory
        ```
        Quantitative evaluation will return:
        1. The sum of all edit (Levenshtein) distance computed across all test pairs
        2. The average edit distance computed across all test pairs
        3. The average normalized edit distance
        4. The average normalized edit similarity
        
        All measure are computed via [textdistance](https://github.com/life4/textdistance).
        
Keywords: seq2seq,ortographic simplification
Platform: any
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Environment :: Web Environment
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
