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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 |