snowflake.ml.model.model_signature.FeatureSpec¶
- class snowflake.ml.model.model_signature.FeatureSpec(name: str, dtype: DataType, shape: Optional[Tuple[int, ...]] = None)¶
Bases:
BaseFeatureSpec
Specification of a feature in Snowflake native model packaging.
Initialize a feature.
- Args:
name: Name of the feature. dtype: Type of the elements in the feature. shape: Used to represent scalar feature, 1-d feature list,
or n-d tensor. Use -1 to represent variable length. Defaults to None.
- Examples:
None: scalar
(2,): 1d list with a fixed length of 2.
(-1,): 1d list with variable length, used for ragged tensor representation.
(d1, d2, d3): 3d tensor.
- Raises:
SnowflakeMLException: TypeError: When the dtype input type is incorrect. SnowflakeMLException: TypeError: When the shape input type is incorrect.
Methods
- as_dtype() Union[dtype[Any], None, Type[Any], _SupportsDType[dtype[Any]], str, Tuple[Any, int], Tuple[Any, Union[SupportsIndex, Sequence[SupportsIndex]]], List[Any], _DTypeDict, Tuple[Any, Any]] ¶
Convert to corresponding local Type.
- as_snowpark_type() DataType ¶
Convert to corresponding Snowpark Type.
- classmethod from_dict(input_dict: Dict[str, Any]) FeatureSpec ¶
Deserialize the feature specification from a dict.
- Args:
input_dict: The dict containing information of the feature specification.
- Returns:
A feature specification instance deserialized and created from the dict.
- classmethod from_mlflow_spec(input_spec: Union[mlflow.types.ColSpec, mlflow.types.TensorSpec], feature_name: str) FeatureSpec ¶
- to_dict() Dict[str, Any] ¶
Serialize the feature group into a dict.
- Returns:
A dict that serializes the feature group.
Attributes
- name¶
Name of the feature.