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import dataclasses
from typing import Any, Dict, List
import datasets
from pytorch_ie.core import (
Annotation,
AnnotationLayer,
AnnotationList,
annotation_field,
)
from pytorch_ie.documents import TextBasedDocument
from pie_datasets import GeneratorBasedBuilder
@dataclasses.dataclass(eq=True, frozen=True)
class AbstractiveSummary(Annotation):
"""A question about a context."""
text: str
def __str__(self) -> str:
return self.text
@dataclasses.dataclass(eq=True, frozen=True)
class SectionName(Annotation):
"""A question about a context."""
text: str
def __str__(self) -> str:
return self.text
@dataclasses.dataclass
class ScientificPapersDocument(TextBasedDocument):
"""A PIE document for scientific papers dataset."""
abstract: AnnotationLayer[AbstractiveSummary] = annotation_field()
section_names: AnnotationList[SectionName] = annotation_field()
def example_to_document(
example: Dict[str, Any],
) -> ScientificPapersDocument:
"""Convert a Huggingface Scientific Papers example to a PIE document."""
document = ScientificPapersDocument(
text=example["article"],
)
document.abstract.append(AbstractiveSummary(text=example["abstract"]))
document.section_names.extend(
[SectionName(text=section_name) for section_name in example["section_names"].split("\n")]
)
return document
def document_to_example(doc: ScientificPapersDocument) -> Dict[str, Any]:
"""Convert a PIE document to a Huggingface Scientific Papers example."""
example = {
"article": doc.text,
"abstract": doc.abstract[0].text,
"section_names": "\n".join([section_name.text for section_name in doc.section_names]),
}
return example
class ScientificPapersConfig(datasets.BuilderConfig):
"""BuilderConfig for Scientific Papers."""
def __init__(self, **kwargs):
"""BuilderConfig for Scientific Papers.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super().__init__(**kwargs)
class ScientificPapers(GeneratorBasedBuilder):
DOCUMENT_TYPE = ScientificPapersDocument
BASE_DATASET_PATH = "scientific_papers"
BASE_DATASET_REVISION = "14c5296f2d707630f5835c9da59dcaddeea19b20"
BUILDER_CONFIGS = [
ScientificPapersConfig(
name="arxiv",
version=datasets.Version("1.1.1"),
description="Scientific Papers dataset - ArXiv variant",
),
ScientificPapersConfig(
name="pubmed",
version=datasets.Version("1.1.1"),
description="Scientific Papers dataset - PubMed variant",
),
]
DEFAULT_CONFIG_NAME = "arxiv"
def _generate_document(self, example, **kwargs):
return example_to_document(example)
def _generate_example(self, document, **kwargs):
return document_to_example(document)
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