trained_model_artifact

Trained model.

Classes:

Name	Description
TrainedModelArtifact	Trained model class, representing a trained model artifact.

TrainedModelArtifact

Trained model class, representing a trained model artifact.

This object is build after finishing a training process, and should never be built manually. It is not allowed to update an instance of it as it is also saved remotely. However, it is still safe to update its name and description

Parameters:

Name	Type	Description	Default
id	str		required
created_at	str		required
created_by	str		required
updated_at	str		required
updated_by	str		required
project_id	str		required
hash_	str		required
private	str		required
name	str		required
description	str		required
core_version	str		required
project	str		required
input_steps	str		required
output_steps	str		required
type_	str		required
checkpoints	str		required
best_checkpoint	str		required

Attributes:

Name	Type	Description
additional_properties	str	dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object's (key, value) pairs dict(iterable) -> new dictionary initialized as if via: d = {} for k, v in iterable: d[k] = v dict(**kwargs) -> new dictionary initialized with the name=value pairs in the keyword argument list. For example: dict(one=1, two=2)

Methods:

Name	Description
__setattr__	Set attribute.
load_all	Load all explanations of the current project.
get_by_id	Get Explanation artifact by its ID.
get_by_name	Get Explanation artifact by its name.
delete	Delete the current object remotely.

__setattr__(attr: str, value: object) -> None

Set attribute.

Source code in src/xpdeep/model/trained_model_artifact.py

@initialized_client_verification
@initialized_project_verification
def __setattr__(self, attr: str, value: object) -> None:
    """Set attribute."""
    if attr in {"name", "description"} and hasattr(self, attr):
        with ClientFactory.CURRENT.get()() as client:
            update_trained_model_artifact.sync(
                Project.CURRENT.get().model.id,
                self.id,
                client=client,
                body=TrainedModelArtifactUpdate(
                    type_="TRAINED_MODEL",
                    name=value if attr == "name" else None,  # type: ignore[arg-type]
                    description=value if attr == "description" else None,  # type: ignore[arg-type]
                ),
            )
    elif hasattr(self, attr) and attr != "additional_properties":
        message = f'Updating attribute "{attr}" is not allowed'
        raise AttributeError(message)

    object.__setattr__(self, attr, value)

load_all() -> list[TrainedModelArtifact]

Load all explanations of the current project.

Source code in src/xpdeep/model/trained_model_artifact.py

@classmethod
@initialized_client_verification
@initialized_project_verification
def load_all(cls) -> list["TrainedModelArtifact"]:
    """Load all explanations of the current project."""
    return [cls.from_dict(select_one.to_dict()) for select_one in cls._load()]

get_by_id(trained_model_id: str) -> TrainedModelArtifact

Get Explanation artifact by its ID.

Parameters:

Name	Type	Description	Default
trained_model_id	str	The ID of the explanation artifact to retrieve.	required

Source code in src/xpdeep/model/trained_model_artifact.py

@classmethod
@initialized_client_verification
@initialized_project_verification
def get_by_id(cls, trained_model_id: str) -> "TrainedModelArtifact":
    """Get Explanation artifact by its ID.

    Parameters
    ----------
    trained_model_id : str
        The ID of the explanation artifact to retrieve.
    """
    try:
        return cls.from_dict(next(iter(cls._load(trained_model_id=trained_model_id))).to_dict())
    except StopIteration as err:
        message = f"No Trained Model artifact found for the ID: {trained_model_id}"
        raise NotSavedError(message) from err

get_by_name(trained_model_id: str) -> TrainedModelArtifact

Get Explanation artifact by its name.

Parameters:

Name	Type	Description	Default
trained_model_id	str	The name of the explanation artifact to retrieve.	required

Source code in src/xpdeep/model/trained_model_artifact.py

@classmethod
@initialized_client_verification
@initialized_project_verification
def get_by_name(cls, trained_model_id: str) -> "TrainedModelArtifact":
    """Get Explanation artifact by its name.

    Parameters
    ----------
    trained_model_id : str
        The name of the explanation artifact to retrieve.
    """
    try:
        return cls.from_dict(next(iter(cls._load(trained_model_name=trained_model_id))).to_dict())
    except StopIteration as err:
        message = f"No Trained Model artifact found for the name: {trained_model_id}"
        raise NotSavedError(message) from err

delete() -> None

Delete the current object remotely.

Source code in src/xpdeep/model/trained_model_artifact.py

@initialized_client_verification
@initialized_project_verification
def delete(self) -> None:
    """Delete the current object remotely."""
    with ClientFactory.CURRENT.get()() as client:
        delete_one_trained_model_artifact.sync(
            Project.CURRENT.get().model.id,
            self.id,
            client=client,
        )