bikes.utils.signers

Generate signatures for AI/ML models.

View Source

 1"""Generate signatures for AI/ML models."""
 2
 3# %% IMPORTS
 4
 5import abc
 6import typing as T
 7
 8import mlflow
 9import pydantic as pdt
10from mlflow.models import signature as ms
11
12from bikes.core import schemas
13
14# %% TYPES
15
16Signature: T.TypeAlias = ms.ModelSignature
17
18# %% SIGNERS
19
20
21class Signer(abc.ABC, pdt.BaseModel, strict=True, frozen=True, extra="forbid"):
22    """Base class for generating model signatures.
23
24    Allow switching between model signing strategies.
25    e.g., automatic inference, manual model signature, ...
26
27    https://mlflow.org/docs/latest/models.html#model-signature-and-input-example
28    """
29
30    KIND: str
31
32    @abc.abstractmethod
33    def sign(self, inputs: schemas.Inputs, outputs: schemas.Outputs) -> Signature:
34        """Generate a model signature from its inputs/outputs.
35
36        Args:
37            inputs (schemas.Inputs): inputs data.
38            outputs (schemas.Outputs): outputs data.
39
40        Returns:
41            Signature: signature of the model.
42        """
43
44
45class InferSigner(Signer):
46    """Generate model signatures from inputs/outputs data."""
47
48    KIND: T.Literal["InferSigner"] = "InferSigner"
49
50    @T.override
51    def sign(self, inputs: schemas.Inputs, outputs: schemas.Outputs) -> Signature:
52        return mlflow.models.infer_signature(model_input=inputs, model_output=outputs)
53
54
55SignerKind = InferSigner

Signature: TypeAlias = mlflow.models.signature.ModelSignature

class Signer(abc.ABC, pydantic.main.BaseModel): View Source

22class Signer(abc.ABC, pdt.BaseModel, strict=True, frozen=True, extra="forbid"):
23    """Base class for generating model signatures.
24
25    Allow switching between model signing strategies.
26    e.g., automatic inference, manual model signature, ...
27
28    https://mlflow.org/docs/latest/models.html#model-signature-and-input-example
29    """
30
31    KIND: str
32
33    @abc.abstractmethod
34    def sign(self, inputs: schemas.Inputs, outputs: schemas.Outputs) -> Signature:
35        """Generate a model signature from its inputs/outputs.
36
37        Args:
38            inputs (schemas.Inputs): inputs data.
39            outputs (schemas.Outputs): outputs data.
40
41        Returns:
42            Signature: signature of the model.
43        """

Base class for generating model signatures.

Allow switching between model signing strategies. e.g., automatic inference, manual model signature, ...

https://mlflow.org/docs/latest/models.html#model-signature-and-input-example

KIND: str

@abc.abstractmethod

def sign( self, inputs: pandera.typing.pandas.DataFrame[bikes.core.schemas.InputsSchema], outputs: pandera.typing.pandas.DataFrame[bikes.core.schemas.OutputsSchema]) -> mlflow.models.signature.ModelSignature: View Source

33    @abc.abstractmethod
34    def sign(self, inputs: schemas.Inputs, outputs: schemas.Outputs) -> Signature:
35        """Generate a model signature from its inputs/outputs.
36
37        Args:
38            inputs (schemas.Inputs): inputs data.
39            outputs (schemas.Outputs): outputs data.
40
41        Returns:
42            Signature: signature of the model.
43        """

Generate a model signature from its inputs/outputs.

Arguments:

inputs (schemas.Inputs): inputs data.
outputs (schemas.Outputs): outputs data.

Returns:

Signature: signature of the model.

model_config: ClassVar[pydantic.config.ConfigDict] = {'strict': True, 'frozen': True, 'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class InferSigner(Signer): View Source

46class InferSigner(Signer):
47    """Generate model signatures from inputs/outputs data."""
48
49    KIND: T.Literal["InferSigner"] = "InferSigner"
50
51    @T.override
52    def sign(self, inputs: schemas.Inputs, outputs: schemas.Outputs) -> Signature:
53        return mlflow.models.infer_signature(model_input=inputs, model_output=outputs)

Generate model signatures from inputs/outputs data.

KIND: Literal['InferSigner']

@T.override

51    @T.override
52    def sign(self, inputs: schemas.Inputs, outputs: schemas.Outputs) -> Signature:
53        return mlflow.models.infer_signature(model_input=inputs, model_output=outputs)