FM / tasks

/usr/local/lib/python3.6/site-packages/datasets/tasks/

/usr/local/lib/python3.6/site-packages/datasets/tasks

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
automatic_speech_recognition.py	1230	0644	edit dl rm
base.py	1095	0644	edit dl rm
image_classification.py	1218	0644	edit dl rm
language_modeling.py	502	0644	edit dl rm
question_answering.py	1026	0644	edit dl rm
summarization.py	693	0644	edit dl rm
text_classification.py	1324	0644	edit dl rm
__init__.py	1482	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/datasets/tasks/question_answering.py (1026B)

from dataclasses import dataclass
from typing import ClassVar, Dict

from ..features import Features, Sequence, Value
from .base import TaskTemplate

@dataclass(frozen=True)
class QuestionAnsweringExtractive(TaskTemplate):
    # `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
    task: str = "question-answering-extractive"
    input_schema: ClassVar[Features] = Features({"question": Value("string"), "context": Value("string")})
    label_schema: ClassVar[Features] = Features(
        {
            "answers": Sequence(
                {
                    "text": Value("string"),
                    "answer_start": Value("int32"),
                }
            )
        }
    )
    question_column: str = "question"
    context_column: str = "context"
    answers_column: str = "answers"

@property
    def column_mapping(self) -> Dict[str, str]:
        return {self.question_column: "question", self.context_column: "context", self.answers_column: "answers"}

from dataclasses import dataclass from typing import ClassVar, Dict from ..features import Features, Sequence, Value from .base import TaskTemplate @dataclass(frozen=True) class QuestionAnsweringExtractive(TaskTemplate): # `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization task: str = "question-answering-extractive" input_schema: ClassVar[Features] = Features({"question": Value("string"), "context": Value("string")}) label_schema: ClassVar[Features] = Features( { "answers": Sequence( { "text": Value("string"), "answer_start": Value("int32"), } ) } ) question_column: str = "question" context_column: str = "context" answers_column: str = "answers" @property def column_mapping(self) -> Dict[str, str]: return {self.question_column: "question", self.context_column: "context", self.answers_column: "answers"}