Move JaxClassifier to experimental

Signed-off-by: Beat Buesser <[email protected]>

Author: Beat Buesser

art/estimators/classification/__init__.py

@@ -14,7 +14,6 @@
 from art.estimators.classification.ensemble import EnsembleClassifier
 from art.estimators.classification.GPy import GPyGaussianProcessClassifier
 from art.estimators.classification.keras import KerasClassifier
-from art.estimators.classification.jax import JaxClassifier
 from art.estimators.classification.lightgbm import LightGBMClassifier
 from art.estimators.classification.mxnet import MXClassifier
 from art.estimators.classification.pytorch import PyTorchClassifier

art/experimental/__init__.py

@@ -0,0 +1,4 @@
+"""
+This module contains the experimental Estimator API.
+"""
+from art.experimental.estimators.jax import JaxEstimator

art/experimental/estimators/__init__.py

@@ -0,0 +1,4 @@
+"""
+Experimental classifiers.
+"""
+from art.experimental.estimators.classification.jax import JaxClassifier

art/experimental/estimators/classification/__init__.py

@@ -30,7 +30,7 @@
     ClassGradientsMixin,
     ClassifierMixin,
 )
-from art.estimators.jax import JaxEstimator
+from art.experimental.estimators.jax import JaxEstimator
 
 if TYPE_CHECKING:
     from art.utils import CLIP_VALUES_TYPE, PREPROCESSING_TYPE

art/estimators/classification/jax.py renamed to art/experimental/estimators/classification/jax.py

@@ -77,7 +77,7 @@
     from art.estimators.classification.ensemble import EnsembleClassifier
     from art.estimators.classification.GPy import GPyGaussianProcessClassifier
     from art.estimators.classification.keras import KerasClassifier
-    from art.estimators.classification.jax import JaxClassifier
+    from art.experimental.estimators.classification.jax import JaxClassifier
     from art.estimators.classification.lightgbm import LightGBMClassifier
     from art.estimators.classification.mxnet import MXClassifier
     from art.estimators.classification.pytorch import PyTorchClassifier
@@ -982,7 +982,6 @@ def load_nursery(raw: bool = False, test_set: float = 0.2, transform_social: boo
     :return: Entire dataset and labels.
     """
     import pandas as pd
-    import sklearn.model_selection
     import sklearn.preprocessing
 
     # Download data if needed

art/estimators/jax.py renamed to art/experimental/estimators/jax.py

@@ -7,7 +7,7 @@
 import jax.numpy as jnp
 from jax.scipy.special import logsumexp
 
-from art.estimators.classification.jax import JaxClassifier
+from art.experimental.estimators.classification.jax import JaxClassifier
 from tests.utils import ARTTestException