gluonts.dataset.arrow.enc module

class gluonts.dataset.arrow.enc.ArrowEncoder(columns: List[str], ndarray_columns: Set[str] = <factory>, flatten_arrays: bool = True)

Bases: object

columns: List[str]

encode(entry: dict)

flatten_arrays: bool = True

classmethod infer(sample: dict, flatten_arrays=True)

ndarray_columns: Set[str]

class gluonts.dataset.arrow.enc.ArrowWriter(stream: bool = False, suffix: str = '.feather', compression: Union[Literal['lz4'], Literal['zstd'], NoneType] = None, flatten_arrays: bool = True, metadata: Optional[dict] = None)

Bases: DatasetWriter

compression: Optional[Union[Literal['lz4'], Literal['zstd']]] = None

flatten_arrays: bool = True

metadata: Optional[dict] = None

stream: bool = False

suffix: str = '.feather'

write_to_file(dataset: Dataset, path: Path) → None

write_to_folder(dataset: Dataset, folder: Path, name: Optional[str] = None) → None

class gluonts.dataset.arrow.enc.ParquetWriter(suffix: str = '.parquet', flatten_arrays: bool = True, metadata: Optional[dict] = None)

Bases: DatasetWriter

flatten_arrays: bool = True

metadata: Optional[dict] = None

suffix: str = '.parquet'

write_to_file(dataset: Dataset, path: Path) → None

write_to_folder(dataset: Dataset, folder: Path, name: Optional[str] = None) → None

gluonts.dataset.arrow.enc.into_arrow_batches(dataset, batch_size=1024, flatten_arrays=True)

gluonts.dataset.arrow.enc.write_dataset(Writer, dataset, path, metadata=None, batch_size=1024, flatten_arrays=True)