IO Descriptors

EvaDB supports three key data types. The inputs and outputs of the functions must be of one of these types.

NumpyArray

Used when the inputs or outputs of the function is of type Numpy Array.

Parameters

name (str): name of the numpy array.

is_nullable (bool): boolean value indicating if the numpy array can be NULL.

type (NdArrayType): data type of all the elements in the numpy array. The available types can be found in evadb/catalog/catalog_type.py in the class NdArrayType

dimensions(Tuple(int)): shape of the numpy array

from evadb.catalog.catalog_type import NdArrayType
NumpyArray(
        name="input_arr",
        is_nullable=False,
        type=NdArrayType.INT32,
        dimensions=(2, 2),
)

PyTorchTensor

name (str): name of the pytorch tensor.

is_nullable (bool): boolean value indicating if the pytorch tensor can be NULL.

type (NdArrayType): data type of elements in the pytorch tensor. The available types can be found in evadb/catalog/catalog_type.py in class NdArrayType

dimensions(Tuple(int)): shape of the numpy array

from evadb.catalog.catalog_type import NdArrayType
PyTorchTensor(
                name="input_arr",
                is_nullable=False,
                type=NdArrayType.INT32,
                dimensions=(2, 2),
)

PandasDataframe

columns (List[str]): list of strings that represent the expected column names in the pandas dataframe that is returned from the function.

column_types (NdArrayType): expected datatype of the column in the pandas dataframe returned from the function. The NdArrayType class is inherited from evadb.catalog.catalog_type.

column_shapes (List[tuples]): list of tuples that represent the expected shapes of columns in the pandas dataframe returned from the function.

PandasDataframe(
            columns=["labels", "bboxes", "scores"],
            column_types=[
                NdArrayType.STR,
                NdArrayType.FLOAT32,
                NdArrayType.FLOAT32,
            ],
            column_shapes=[(None,), (None,), (None,)],
)