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import json
import datasets
logger = datasets.logging.get_logger(__name__)
_URL = "https://huggingface.co/datasets/sagnikrayc/snli-bt/resolve/main"
_URLS = {
"train": f"{_URL}/train.jsonl",
"validation": f"{_URL}/validation.jsonl",
"test": f"{_URL}/test.jsonl",
}
class SnliBTConfig(datasets.BuilderConfig):
def __init__(self, **kwargs):
super(SnliBTConfig, self).__init__(**kwargs)
class SnliCF(datasets.GeneratorBasedBuilder):
"""SQUAD: The Stanford Question Answering Dataset. Version 1.1."""
BUILDER_CONFIGS = [
SnliBTConfig(
name="plain_text",
version=datasets.Version("1.0.0", ""),
description="Plain text",
),
]
def _info(self):
return datasets.DatasetInfo(
description="NA",
features=datasets.Features(
{
"idx": datasets.Value("string"),
"premise": datasets.Value("string"),
"hypothesis": datasets.Value("string"),
"label": datasets.Value("string"),
"_type": datasets.Value("string"),
}
),
# No default supervised_keys (as we have to pass both question
# and context as input).
supervised_keys=None
)
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["validation"]}
),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
]
def _generate_examples(self, filepath):
"""This function returns the examples in the raw (text) form."""
logger.info("generating examples from = %s", filepath)
with open(filepath, encoding="utf-8") as rf:
for idx, line in enumerate(rf):
if line:
_line = json.loads(line)
yield idx, {
"premise": _line["premise"],
"hypothesis": _line["hypothesis"],
"idx": _line["idx"],
"_type": _line["_type"],
"label": _line["label"]
} |