File size: 2,864 Bytes
ab0b497 6ef1e09 ab0b497 102907e 2711314 102907e ab0b497 6ef1e09 ab0b497 |
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 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 |
"""C4 dataset based on Common Crawl."""
import gzip
import json
import datasets
try:
import lzma as xz
except ImportError:
import pylzma as xz
logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """\
A living legal dataset.
"""
_CITATION = """
TODO
"""
_URL = ""
_DATA_URL = {
"eoir_privacy" :
{
"train" : ["https://huggingface.co/datasets/pile-of-law/eoir_privacy/resolve/main/data/train.privacy.eoir.jsonl.xz"],
"validation" : ["https://huggingface.co/datasets/pile-of-law/eoir_privacy/resolve/main/data/validation.privacy.eoir.jsonl.xz"]
}
}
_VARIANTS = ["all"] + list(_DATA_URL.keys())
class EOIRPrivacy(datasets.GeneratorBasedBuilder):
"""TODO"""
BUILDER_CONFIGS = [datasets.BuilderConfig(name) for name in _VARIANTS]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"text": datasets.Value("string"),
"year": datasets.Value("string"),
"name": datasets.Value("string"),
'label': datasets.ClassLabel(num_classes=2, names=['False', 'True'])
}
),
supervised_keys=None,
homepage=_URL,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
data_urls = {}
if self.config.name == "all":
data_sources = list(_DATA_URL.keys())
else:
data_sources = [self.config.name]
for split in ["train", "validation"]:
data_urls[split] = []
for source in data_sources:
for chunk in _DATA_URL[source][split]:
data_urls[split].append(chunk)
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 xz.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
for line in f:
if line:
example = json.loads(line)
label = example["label"]
example["label"] = int(label)
yield id_, example
id_ += 1
|