File size: 2,260 Bytes
43857a6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
import json
import datasets
import gzip

logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """\\nRomanian diacritic dataset"""
_CITATION = """n/a"""

_URL = "https://github.com/dumitrescustefan/diacritic"
_DATA_URL = "https://huggingface.co/datasets/dumitrescustefan/diacritic/resolve/main/data/{split_suffix}-{index:03d}.json.gz"
_N_SHARDS_PER_SPLIT = {
    "train": 78, "validation": 1
}

class RLM(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name="v1", version="1.0.0", description="v1.0 of romanian diacritic corpus"),
    ]

    DEFAULT_CONFIG_NAME = "v1"

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "id": datasets.Value("int64"),
                    "text": datasets.Value("string"),
                }
            ),
            supervised_keys=None,
            homepage=_URL,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        data_urls = {}
        for split in ["train", "validation"]:
            data_urls[split] = [
                _DATA_URL.format(split_suffix=split, index=iindex) for iindex in range(_N_SHARDS_PER_SPLIT[split])
                    ]

        train_downloaded_files = dl_manager.download(data_urls["train"])
        validation_downloaded_files = dl_manager.download(data_urls["validation"])

        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": train_downloaded_files}),
            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepaths": validation_downloaded_files}),
               ]

    def _generate_examples(self, filepaths):
        """This function returns the examples in the raw (text) form by iterating on all the files."""
        id_ = 0
        for filepath in filepaths:
            logger.info("generating examples from = %s", filepath)
            with gzip.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
                for line in f:
                    if line:
                        example = json.loads(line)
                        yield id_, example
                        id_ += 1