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# coding=utf-8
'''DiscEvalMT: DiscEvalMT: Contrastive test sets for the evaluation of discourse in machine translation (v2)'''

import json
import datasets

logger = datasets.logging.get_logger(__name__)

_CITATION = '''\
@inproceedings{bawden-etal-2018-evaluating,
    title = "Evaluating Discourse Phenomena in Neural Machine Translation",
    author = "Bawden, Rachel and Sennrich, Rico and Birch, Alexandra and Haddow, Barry",
    booktitle = {{Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)}},
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/N18-1118",
    doi = "10.18653/v1/N18-1118",
    pages = "1304--1313"
}
'''

_DESCRIPTION = '''\
English-French hand-crafted contrastive test set to test anaphora and lexical choice
'''

_HOMEPAGE='https://github.com/rbawden/discourse-mt-test-sets/tree/master'

_LICENSE = 'CC-BY-SA-4.0'
 
_URLS = {
    'test-lexical_choice': 'lexical_choice/eval.jsonl',
    'test-anaphora': 'anaphora/eval.jsonl'
}


class DiscEvalMTConfig(datasets.BuilderConfig):
    '''BuilderConfig for DiscEvalMT.'''
    

    def __init__(self, evaltype: str, **kwargs):
        """BuilderConfig for DiscEvalMT.

        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        self.evaltype = evaltype
        if evaltype not in ['anaphora', 'lexical_choice']:
            raise ValueError("Invalid evaltype: %s. You must choose between 'anaphora' and 'lexical_choice' " % evaltype)
        super(DiscEvalMTConfig, self).__init__(**kwargs)

        


class DiscEvalMT(datasets.GeneratorBasedBuilder):
    '''DiscEvalMT: English-French contrastive test set for 2 discourse phenomena (anaphora and lexical cohesion)'''

    BUILDER_CONFIG_CLASS = DiscEvalMTConfig
    BUILDER_CONFIGS = [
        DiscEvalMTConfig(
            evaltype='anaphora',
            name='anaphora',
            version=datasets.Version('2.0.0'),
        ),
        DiscEvalMTConfig(
            evaltype='lexical_choice',
            name='lexical_choice',
            version=datasets.Version('2.0.0'),
        ),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features({
                                        "split": datasets.Value("string"), 
                                        "ex_num": datasets.Value("int64"),
                                        "type": datasets.Value("string"),
                                        "context_src": datasets.Value("string"),
                                        "current_src": datasets.Value("string"),
                                        "context_trg": datasets.Value("string"),
                                        "current_trg": datasets.Value("string"),
                                        "contrastive_context_trg": datasets.Value("string"),
                                        "contrastive_current_trg": datasets.Value("string"),
                                        "correct_or_semicorrect": datasets.Value("string")}),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            citation=_CITATION,
            license=_LICENSE,
        )

    def _split_generators(self, dl_manager):
        downloaded_files = dl_manager.download_and_extract(_URLS)

        return datasets.SplitGenerator(name="test", gen_kwargs={'filepath': downloaded_files['test-' + self.config.evaltype]}),
               

    def _generate_examples(self, filepath):
        logger.info("generating examples from = %s", filepath)
        key = 0
        with open(filepath, encoding="utf-8") as f:
            for i, line in enumerate(f):
                
                example = json.loads(line)
                print(example.keys())
                yield i, example