PreprocessResponse

code_loader.contract.datasetclasses.PreprocessResponse

An object that holds the samples data and length. This object is generated in the Preprocessing Function for each dataset slice. Then passed to the input encoders, ground_truth encoders and metadata functions as an argument.

from code_loader.contract.enums import DataStateType

@dataclass
PreprocessResponse:
    length: Optional[int] = None,
    data: Any = None,
    sample_ids: Optional[Union[List[str], List[int]]] = None,
    state: Optional[DataStateType] = None,
    sample_id_type: Optional[Union[Type[str], Type[int]]] = None

For more on PreprocessResponse:

Args
length	(int) value with the amount of samples in the data.
data	(Any) Dictionary / pandas.DataFrame / List or any object that describes the dataset features. The data parameter is later passed to the input encoders, ground_truth encoders, and metadata functions.
sample_ids	(optional) a list of unique identifiers for the input, of the same length as your dataset. IDs should be either a list of ints or strings
state	(DataStateType, optional). Defaults to None. If this is not supplied the state is infered according to its order an is estimated to be [training, validatin, test, unlabeled]
sample_id_type	(str/int, optional). What is the type of the sample_id if provided.

Examples

Basic Usage

from code_loader.contract.datasetclasses import PreprocessResponse
preprocess_response = PreprocessResponse(length=len(x_df.index), data=x_df)

Within the Preprocess Function

Full examples can be found at the Dataset Integration section of the following guides:

• MNIST Guide

• IMDB Guide