Delete diabla.py

diabla.py

@@ -1,134 +0,0 @@
-# coding=utf-8
-'''DiaBLA: Dialogue Bilingue datset'''
-
-import json
-import datasets
-
-
-logger = datasets.logging.get_logger(__name__)
-
-_CITATION = '''\
-@article{bawden_DiaBLa:-A-Corpus-of_2021,
-  author = {Bawden, Rachel and Bilinski, Eric and Lavergne, Thomas and Rosset, Sophie},
-  doi = {10.1007/s10579-020-09514-4},
-  title = {DiaBLa: A Corpus of Bilingual Spontaneous Written Dialogues for Machine Translation},
-  year = {2021},
-  journal = {Language Resources and Evaluation},
-  publisher = {Springer Verlag},
-  volume = {55},
-  pages = {635--660},
-  url = {https://hal.inria.fr/hal-03021633},
-  pdf = {https://hal.inria.fr/hal-03021633/file/diabla-lre-personal-formatting.pdf},
-}
-'''
-
-_DESCRIPTION = '''\
-English-French parallel dataset for the evaluation of \
-Machine Translation (MT) for informal, written bilingual dialogue.
-'''
- 
-#_URL = 'https://github.com/rbawden/DiaBLa-dataset'
-#_URLS = {
-#    'dialogues': _URL + '/DiaBLa-corpus/all-dialogues.json',
-#    'users': _URL + '/DiaBLa-corpus/all-users.json'
-#}
-
-
-class DiablaConfig(datasets.BuilderConfig):
-    '''BuilderConfig for DiaBLa.'''
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for SQUAD.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(SquadConfig, self).__init__(**kwargs)
-
-
-class Diabla(datasets.GeneratorBasedBuilder):
-    '''DiaBLa: English-French parallel dataset of bilingual dialogue'''
-
-    BUILDER_CONFIGS = [
-        SquadConfig(
-            name="plain_text",
-            version=datasets.Version("1.0.0", ""),
-            description="Plain text",
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "title": datasets.Value("string"),
-                    "context": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    "answers": datasets.features.Sequence(
-                        {
-                            "text": datasets.Value("string"),
-                            "answer_start": datasets.Value("int32"),
-                        }
-                    ),
-                }
-            ),
-            # No default supervised_keys (as we have to pass both question
-            # and context as input).
-            supervised_keys=None,
-            homepage='https://github.com/rbawden/DiaBLa-dataset'
-            citation=_CITATION,
-            task_templates=[
-                # TODO
-            ],
-        )
-
-    #def _split_generators(self, dl_manager):
-    #    downloaded_files = dl_manager.download_and_extract(_URLS)
-
-    #    return [
-    #        datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-    #        datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-    #    ]
-
-    def _generate_examples(self, filepath):
-        '''This function returns the examples in the raw (text) form.'''
-        logger.info("generating examples from = %s", filepath)
-        key = 0
-        with open(filepath, encoding="utf-8") as f:
-            diabla = json.load(f)
-            for dialogue_name in sorted(diabla['dialogues']):
-                dialogue_history = [] # to store past utterances
-                dialogue = diabla['dialogues'][dialogue_name]
-                # Meta-information attached to the dialogue
-                dialogue_info_keys = ['start_time', 'end_time', 'scenario',
-                                      'user1', 'user2', 'translation_model',
-                                      'final_evaluation_user1', 'final_evaluation_user2']
-                dialogue_info = {k: dialogue[k] for k in dialogue_info_keys}
-                # Main data: the utterances
-                for utterance_id in dialogue['utterances']:
-                    utterance = utterances[utterance_id]
-                    # Meta-information attached to the utterance
-                    utterance_info_keys = ['judgment', 'verbatim', 'problems', 'user']
-                    utterance_info = {'eval-' + k: utterance['eval'][k] for k in utterance_info_keys}
-                    utterance_info['language'] = utterance['language']
-                    # Utterance text
-                    original_text = utterance['original_text']
-                    mt_text = utterance['postprocessed_text']
-                    reference_text = utterance['reference_translation']
-                    normalised_text = utterance['normalised_version']
-                    id_ = dialogue_name + '_' + utterance_id
-                    utterance_instance = {
-                        'orig_text': original_text,
-                        'norm_text': normalised_text,
-                        'mt_text': mt_text,
-                        'id': id_,
-                        'ref_text': reference_text,
-                        'utterance_meta_info': utterance_info
-                        'context': dialogue_history
-                    }
-                    # add to history (without dialogue info)
-                    dialogue_history.append(utterance_instance.copy()) 
-                    utterance_instance['dialogue_meta_info'] = utterance_info
-                    yield id_, utterance_instance