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import json
import gzip
import datasets
import os
_CITATION = """\
"""
_DESCRIPTION = """\
"""
_HOMEPAGE = ""
_LICENSE = ""
# TODO: Add link to the official dataset URLs here
_FILES = {
'0': ['part_0_0.jsonl.gz', 'part_0_1.jsonl.gz', 'part_0_2.jsonl.gz'],
'1': ['part_1_0.jsonl.gz', 'part_1_1.jsonl.gz', 'part_1_2.jsonl.gz'],
'2': ['part_2_0.jsonl.gz', 'part_2_1.jsonl.gz', 'part_2_2.jsonl.gz'],
'3': ['part_3_0.jsonl.gz', 'part_3_1.jsonl.gz', 'part_3_2.jsonl.gz'],
'4': ['part_4_0.jsonl.gz', 'part_4_1.jsonl.gz', 'part_4_2.jsonl.gz'],
'5': ['part_5_0.jsonl.gz', 'part_5_1.jsonl.gz', 'part_5_2.jsonl.gz'],
'6': ['part_6_0.jsonl.gz', 'part_6_1.jsonl.gz'],
'7': ['part_7_0.jsonl.gz', 'part_7_1.jsonl.gz', 'part_7_2.jsonl.gz'],
'8': ['part_8_0.jsonl.gz', 'part_8_1.jsonl.gz'],
'9': ['part_9_0.jsonl.gz', 'part_9_1.jsonl.gz'],
'10': ['part_10_0.jsonl.gz', 'part_10_1.jsonl.gz'],
'11': ['part_11_0.jsonl.gz', 'part_11_1.jsonl.gz'],
'12': ['part_12_0.jsonl.gz', 'part_12_1.jsonl.gz'],
'13': ['part_13_0.jsonl.gz', 'part_13_1.jsonl.gz'],
'14': ['part_14_0.jsonl.gz', 'part_14_1.jsonl.gz']
}
_URLS = {
"all_data": "data/all_data"
}
# TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
class OAGKx(datasets.GeneratorBasedBuilder):
"""TODO: Short description of my dataset."""
VERSION = datasets.Version("0.0.1")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="extraction", version=VERSION,
description="This part of my dataset covers extraction"),
datasets.BuilderConfig(name="generation", version=VERSION,
description="This part of my dataset covers generation"),
datasets.BuilderConfig(name="raw", version=VERSION, description="This part of my dataset covers the raw data"),
]
DEFAULT_CONFIG_NAME = "extraction"
def _info(self):
_URLS['all_data']=['data/' + filename for part in _FILES for filename in _FILES[part]]
if self.config.name == "extraction": # This is the name of the configuration selected in BUILDER_CONFIGS above
features = datasets.Features(
{
"id": datasets.Value("int64"),
"document": datasets.features.Sequence(datasets.Value("string")),
"doc_bio_tags": datasets.features.Sequence(datasets.Value("string"))
}
)
elif self.config.name == "generation":
features = datasets.Features(
{
"id": datasets.Value("int64"),
"document": datasets.features.Sequence(datasets.Value("string")),
"extractive_keyphrases": datasets.features.Sequence(datasets.Value("string")),
"abstractive_keyphrases": datasets.features.Sequence(datasets.Value("string"))
}
)
else:
features = datasets.Features(
{
"id": datasets.Value("int64"),
"document": datasets.features.Sequence(datasets.Value("string")),
"doc_bio_tags": datasets.features.Sequence(datasets.Value("string")),
"extractive_keyphrases": datasets.features.Sequence(datasets.Value("string")),
"abstractive_keyphrases": datasets.features.Sequence(datasets.Value("string")),
"other_metadata": datasets.features.Sequence(
{
"text": datasets.features.Sequence(datasets.Value("string")),
"bio_tags": datasets.features.Sequence(datasets.Value("string"))
}
)
}
)
return datasets.DatasetInfo(
# This is the description that will appear on the datasets page.
description=_DESCRIPTION,
# This defines the different columns of the dataset and their types
features=features,
homepage=_HOMEPAGE,
# License for the dataset if available
license=_LICENSE,
# Citation for the dataset
citation=_CITATION,
)
def _split_generators(self, dl_manager):
data_dir = dl_manager.download_and_extract(_URLS)
print(data_dir["all_data"])
return [
datasets.SplitGenerator(
name="all_data",
# These kwargs will be passed to _generate_examples
gen_kwargs={
"filepaths": data_dir["all_data"],
"split": "all_data",
},
),
]
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
def _generate_examples(self, filepaths, split):
for filepath in filepaths:
with open(filepath, encoding="utf-8") as f:
for key, row in enumerate(f):
data = json.loads(row)
if self.config.name == "extraction":
# Yields examples as (key, example) tuples
yield key, {
"id": data.get("paper_id"),
"document": data["document"],
"doc_bio_tags": data.get("doc_bio_tags")
}
elif self.config.name == "generation":
yield key, {
"id": data.get("paper_id"),
"document": data["document"],
"extractive_keyphrases": data.get("extractive_keyphrases"),
"abstractive_keyphrases": data.get("abstractive_keyphrases")
}
else:
yield key, {
"id": data.get("paper_id"),
"document": data["document"],
"doc_bio_tags": data.get("doc_bio_tags"),
"extractive_keyphrases": data.get("extractive_keyphrases"),
"abstractive_keyphrases": data.get("abstractive_keyphrases"),
"other_metadata": data["other_metadata"]
}
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