snowflake.ml.model.model_signature.infer_signature¶

snowflake.ml.model.model_signature.infer_signature(input_data: Union[pd.DataFrame, ndarray[Any, dtype[Union[np.int8, np.int16, np.int32, np.int64, np.float32, np.float64, np.uint8, np.uint16, np.uint32, np.uint64, np.bool_, np.str_, np.bytes_]]], Sequence[Union[ndarray[Any, dtype[Union[np.int8, np.int16, np.int32, np.int64, np.float32, np.float64, np.uint8, np.uint16, np.uint32, np.uint64, np.bool_, np.str_, np.bytes_]]], torch.Tensor, tensorflow.Tensor, tensorflow.Variable]], Sequence[Union[int, float, bool, str, bytes, _SupportedBuiltinsList]]], output_data: Union[pd.DataFrame, ndarray[Any, dtype[Union[np.int8, np.int16, np.int32, np.int64, np.float32, np.float64, np.uint8, np.uint16, np.uint32, np.uint64, np.bool_, np.str_, np.bytes_]]], Sequence[Union[ndarray[Any, dtype[Union[np.int8, np.int16, np.int32, np.int64, np.float32, np.float64, np.uint8, np.uint16, np.uint32, np.uint64, np.bool_, np.str_, np.bytes_]]], torch.Tensor, tensorflow.Tensor, tensorflow.Variable]], Sequence[Union[int, float, bool, str, bytes, _SupportedBuiltinsList]]], input_feature_names: Optional[List[str]] = None, output_feature_names: Optional[List[str]] = None) → ModelSignature¶

Infer model signature from given input and output sample data.

Currently supports inferring model signatures from the following data types:

• Pandas DataFrame with columns of supported data types, lists (including nested lists) of supported data types,

  and NumPy arrays of supported data types. - Does not support DataFrame with CategoricalIndex column index.

• NumPy arrays of supported data types.

• Lists of NumPy arrays of supported data types.

• Lists of supported data types or nested lists of supported data types.

When inferring the signature, a ValueError indicates that the data is insufficient or invalid.

When it might be possible to create a signature reflecting the provided data, but it could not be inferred, a NotImplementedError is raised

Args:

input_data: Sample input data for the model. output_data: Sample output data for the model. input_feature_names: Names for input features. Defaults to None. output_feature_names: Names for output features. Defaults to None.

Returns:

A model signature inferred from the given input and output sample data.