Buckets:
| from abc import ABC, abstractmethod | |
| from typing import Optional, Union | |
| from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit | |
| from ..utils.typing import NestedDataStructureLike, PathLike | |
| class AbstractDatasetReader(ABC): | |
| def __init__( | |
| self, | |
| path_or_paths: Optional[NestedDataStructureLike[PathLike]] = None, | |
| split: Optional[NamedSplit] = None, | |
| features: Optional[Features] = None, | |
| cache_dir: str = None, | |
| keep_in_memory: bool = False, | |
| streaming: bool = False, | |
| num_proc: Optional[int] = None, | |
| **kwargs, | |
| ): | |
| self.path_or_paths = path_or_paths | |
| self.split = split if split or isinstance(path_or_paths, dict) else "train" | |
| self.features = features | |
| self.cache_dir = cache_dir | |
| self.keep_in_memory = keep_in_memory | |
| self.streaming = streaming | |
| self.num_proc = num_proc | |
| self.kwargs = kwargs | |
| def read(self) -> Union[Dataset, DatasetDict, IterableDataset, IterableDatasetDict]: | |
| pass | |
| class AbstractDatasetInputStream(ABC): | |
| def __init__( | |
| self, | |
| features: Optional[Features] = None, | |
| cache_dir: str = None, | |
| keep_in_memory: bool = False, | |
| streaming: bool = False, | |
| num_proc: Optional[int] = None, | |
| **kwargs, | |
| ): | |
| self.features = features | |
| self.cache_dir = cache_dir | |
| self.keep_in_memory = keep_in_memory | |
| self.streaming = streaming | |
| self.num_proc = num_proc | |
| self.kwargs = kwargs | |
| def read(self) -> Union[Dataset, IterableDataset]: | |
| pass | |
Xet Storage Details
- Size:
- 1.67 kB
- Xet hash:
- 2816c3d92c6ef47536f6cdcbb4d43e0e15843fb41f183c7e0c8c643c9ec0f4c6
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.