| import dataclasses |
| from typing import Any, Dict, List |
|
|
| import datasets |
| from pie_core import Annotation, AnnotationLayer, annotation_field |
| from pie_documents.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: AnnotationLayer[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) |
|
|