unienv_data.batches.transformations

TransformedBatch

TransformedBatch(batch: BatchBase[SourceDataT, SourceBArrT, SourceBDeviceT, SourceBDTypeT, SourceBDRNGT], transformation: DataTransformation, metadata_transformation: Optional[DataTransformation] = None)

Bases: BatchBase[BatchT, BArrayType, BDeviceType, BDtypeType, BRNGType]

batch instance-attribute

batch = batch

transformation instance-attribute

transformation = transformation

metadata_transformation instance-attribute

metadata_transformation = metadata_transformation if single_metadata_space is not None else None

backend property

backend: ComputeBackend[BArrayType, BDeviceType, BDtypeType, BRNGType]

device property

device: Optional[BDeviceType]

is_mutable property

is_mutable: bool

single_space instance-attribute

single_space = single_space

single_metadata_space instance-attribute

single_metadata_space = single_metadata_space

get_flattened_at

get_flattened_at(idx: Union[IndexableType, BArrayType]) -> BArrayType

get_flattened_at_with_metadata

get_flattened_at_with_metadata(idx: Union[IndexableType, BArrayType]) -> Tuple[BArrayType, Optional[Dict[str, Any]]]

set_flattened_at

set_flattened_at(idx: Union[IndexableType, BArrayType], value: BArrayType) -> None

extend_flattened

extend_flattened(value: BArrayType) -> None

get_at

get_at(idx: Union[IndexableType, BArrayType] = None) -> BatchT

get_at_with_metadata

get_at_with_metadata(idx: Union[IndexableType, BArrayType]) -> Tuple[BatchT, Optional[Dict[str, Any]]]

set_at

set_at(idx: Union[IndexableType, BArrayType], value: BatchT) -> None

remove_at

remove_at(idx: Union[IndexableType, BArrayType]) -> None

extend

extend(value: BatchT) -> None

close

close()

append_flattened

append_flattened(value: BArrayType) -> None

Append one flattened sample to the batch.

append

append(value: BatchT) -> None

Append one structured sample to the batch.

extend_from

extend_from(other: BatchBase[BatchT, BArrayType, BDeviceType, BDtypeType, BRNGType], chunk_size: int = 8, tqdm: bool = False) -> None

Copy data from another batch in bounded-size chunks.

get_slice

get_slice(idx: Union[IndexableType, BArrayType]) -> BatchBase[BatchT, BArrayType, BDeviceType, BDtypeType, BRNGType]

Create a lazy view over a subset of indices.

get_column

get_column(nested_keys: Sequence[str]) -> BatchBase[Any, BArrayType, BDeviceType, BDtypeType, BRNGType]

Create a lazy view over a nested field inside each sample.