registry#
Note
See the Glossary for the meaning of the acronyms used in this guide.
art.py#
A task plugin module for interfacing the Adversarial Robustness Toolbox with the MLFlow model registry.
- load_wrapped_tensorflow_keras_classifier(name: str, version: int, imagenet_preprocessing: bool = False, classifier_kwargs: Optional[Dict[str, Any]] = None) art.estimators.classification.TensorFlowV2Classifier [source]#
Loads and wraps a registered Keras classifier for compatibility with the Adversarial Robustness Toolbox.
- Parameters
name – The name of the registered model in the MLFlow model registry.
version – The version number of the registered model in the MLFlow registry.
classifier_kwargs – A dictionary mapping argument names to values which will be passed to the TensorFlowV2Classifier constructor.
- Returns
- A trained
TensorFlowV2Classifier
object.
- A trained
mlflow.py#
A task plugin module for using the MLFlow model registry.
- add_model_to_registry(active_run: mlflow.entities.Run, name: str, model_dir: str) Optional[mlflow.entities.model_registry.ModelVersion] [source]#
Registers a trained model logged during the current run to the MLFlow registry.
- Parameters
active_run – The
mlflow.ActiveRun
object managing the current run’s state.name – The registration name to use for the model.
model_dir – The relative artifact directory where MLFlow logged the model trained during the current run.
- Returns
A
ModelVersion
object created by the backend.
- get_experiment_name(active_run: mlflow.entities.Run) str [source]#
Gets the name of the experiment for the current run.
- Parameters
active_run – The
mlflow.ActiveRun
object managing the current run’s state.- Returns
The name of the experiment.
- load_tensorflow_keras_classifier(name: str, version: int) tensorflow.keras.models.Sequential [source]#
Loads a registered Keras classifier.
- Parameters
name – The name of the registered model in the MLFlow model registry.
version – The version number of the registered model in the MLFlow registry.
- Returns
A trained
tf.keras.Sequential
object.