Metadata-Version: 2.1
Name: code2seq
Version: 0.0.2
Summary: Set of pytorch modules and utils to train code2seq model
Home-page: https://github.com/JetBrains-Research/code2seq
Author: Egor Spirin
Author-email: spirin.egor@gmail.com
License: MIT
Download-URL: https://pypi.org/project/code2seq/
Description: # code2seq
        
        [![JetBrains Research](https://jb.gg/badges/research.svg)](https://confluence.jetbrains.com/display/ALL/JetBrains+on+GitHub)
        [![Github action: build](https://github.com/SpirinEgor/code2seq/workflows/Build/badge.svg)](https://github.com/SpirinEgor/code2seq/actions?query=workflow%3ABuild)
        [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
        
        
        PyTorch's implementation of code2seq model.
        
        ## Installation
        
        You can easily install model through the PIP:
        ```shell
        pip install code2seq
        ```
        
        ## Usage
        
        Minimal code example to run the model:
        ```python
        from os.path import join
        
        import hydra
        from code2seq.dataset import PathContextDataModule
        from code2seq.model import Code2Seq
        from code2seq.utils.vocabulary import Vocabulary
        from omegaconf import DictConfig
        from pytorch_lightning import Trainer
        
        
        @hydra.main(config_path="configs")
        def train(config: DictConfig):
            vocabulary_path = join(config.data_folder, config.dataset.name, config.vocabulary_name)
            vocabulary = Vocabulary.load_vocabulary(vocabulary_path)
            model = Code2Seq(config, vocabulary)
            data_module = PathContextDataModule(config, vocabulary)
        
            trainer = Trainer(max_epochs=config.hyper_parameters.n_epochs)
            trainer.fit(model, datamodule=data_module)
        
        
        if __name__ == "__main__":
            train()
        ```
        
        Navigate to [code2seq/configs](code2seq/configs) to see examples of configs.
        If you had any questions then feel free to open the issue.
Keywords: code2seq,pytorch,pytorch-lightning,ml4code,ml4se
Platform: UNKNOWN
Description-Content-Type: text/markdown
