fairlearn · romanlutz · Jun 29, 2021 · Jun 16, 2021 · Jun 25, 2021 · Jun 26, 2021
diff --git a/fairlearn/postprocessing/_interpolated_thresholder.py b/fairlearn/postprocessing/_interpolated_thresholder.py
@@ -10,14 +10,14 @@
 from warnings import warn
 
 from ..utils._common import _get_soft_predictions
-from .._input_validation import _validate_and_reformat_input
+from ..utils._input_validation import _validate_and_reformat_input
 from ._constants import (
     BASE_ESTIMATOR_NONE_ERROR_MESSAGE,
     BASE_ESTIMATOR_NOT_FITTED_WARNING)
 
 
 class InterpolatedThresholder(BaseEstimator, MetaEstimatorMixin):
-    """Binary predictor that thresholds continuous predictions of a base estimator.
+    r"""Binary predictor that thresholds continuous predictions of a base estimator.
 
     At prediction time, the predictor takes as input both standard and sensitive features.
     Based on the values of sensitive features, it then applies a randomized thresholding

diff --git a/fairlearn/postprocessing/_threshold_optimizer.py b/fairlearn/postprocessing/_threshold_optimizer.py
@@ -29,7 +29,7 @@
 from sklearn.utils import Bunch
 
 from ..utils._common import _get_soft_predictions
-from .._input_validation import (
+from ..utils._input_validation import (
     _validate_and_reformat_input,
     _KW_CONTROL_FEATURES,
 )

diff --git a/fairlearn/reductions/_moments/bounded_group_loss.py b/fairlearn/reductions/_moments/bounded_group_loss.py
@@ -6,7 +6,7 @@
 from .moment import LossMoment
 from .moment import _GROUP_ID, _LABEL, _LOSS, _PREDICTION, _ALL
 
-from fairlearn._input_validation import _validate_and_reformat_input
+from fairlearn.utils._input_validation import _validate_and_reformat_input
 
 
 class ConditionalLossMoment(LossMoment):

diff --git a/fairlearn/reductions/_moments/error_rate.py b/fairlearn/reductions/_moments/error_rate.py
@@ -6,7 +6,7 @@
 from .moment import ClassificationMoment
 from .moment import _ALL, _LABEL
 
-from fairlearn._input_validation import _validate_and_reformat_input
+from fairlearn.utils._input_validation import _validate_and_reformat_input
 
 
 class ErrorRate(ClassificationMoment):

diff --git a/fairlearn/reductions/_moments/utility_parity.py b/fairlearn/reductions/_moments/utility_parity.py
@@ -6,7 +6,10 @@
 
 from .moment import ClassificationMoment
 from .moment import _GROUP_ID, _LABEL, _PREDICTION, _ALL, _EVENT, _SIGN
-from fairlearn._input_validation import _MESSAGE_RATIO_NOT_IN_RANGE, _validate_and_reformat_input
+from fairlearn.utils._input_validation import (
+    _MESSAGE_RATIO_NOT_IN_RANGE,
+    _validate_and_reformat_input
+)
 from .error_rate import ErrorRate
 
 

diff --git a/fairlearn/utils/__init__.py b/fairlearn/utils/__init__.py
@@ -0,0 +1,4 @@
 # Copyright (c) Fairlearn contributors.
+# Licensed under the MIT License.
+
+"""This module contains utilities for Fairlearn."""
diff --git a/fairlearn/utils/_common.py b/fairlearn/utils/_common.py
@@ -2,7 +2,7 @@
 # Licensed under the MIT License.
 
 def _get_soft_predictions(estimator, X, predict_method):
-    """Return soft predictions of a classifier.
+    r"""Return soft predictions of a classifier.
 
     Parameters
     ----------

diff --git a/fairlearn/_input_validation.py → fairlearn/utils/_input_validation.py b/fairlearn/_input_validation.py → fairlearn/utils/_input_validation.py
diff --git a/test/unit/input_convertors.py b/test/unit/input_convertors.py
@@ -4,7 +4,7 @@
 import numpy as np
 import pandas as pd
 
-from fairlearn._input_validation import _merge_columns
+from fairlearn.utils._input_validation import _merge_columns
 
 
 def ensure_list(X):

diff --git a/test/unit/postprocessing/test_threshold_optimization.py b/test/unit/postprocessing/test_threshold_optimization.py
@@ -7,15 +7,14 @@
 from copy import deepcopy
 import numpy as np
 import pytest
-from fairlearn._input_validation import \
-    (_MESSAGE_Y_NONE,
-     _MESSAGE_SENSITIVE_FEATURES_NONE,
-     _LABELS_NOT_0_1_ERROR_MESSAGE)
+from fairlearn.utils._input_validation import (
+    _MESSAGE_Y_NONE,
+    _MESSAGE_SENSITIVE_FEATURES_NONE,
+    _LABELS_NOT_0_1_ERROR_MESSAGE)
 from fairlearn.postprocessing import ThresholdOptimizer
-from fairlearn.postprocessing._threshold_optimizer import \
-    (NOT_SUPPORTED_CONSTRAINTS_ERROR_MESSAGE,
-     BASE_ESTIMATOR_NONE_ERROR_MESSAGE,
-     )
+from fairlearn.postprocessing._threshold_optimizer import (
+    NOT_SUPPORTED_CONSTRAINTS_ERROR_MESSAGE,
+    BASE_ESTIMATOR_NONE_ERROR_MESSAGE)
 from fairlearn.postprocessing._tradeoff_curve_utilities import DEGENERATE_LABELS_ERROR_MESSAGE
 from .conftest import (sensitive_features_ex1, labels_ex, degenerate_labels_ex,
                        scores_ex, sensitive_feature_names_ex1, X_ex,

diff --git a/test/unit/reductions/exponentiated_gradient/test_exponentiatedgradient_arguments.py b/test/unit/reductions/exponentiated_gradient/test_exponentiatedgradient_arguments.py
@@ -11,7 +11,7 @@
 from fairlearn.reductions import ExponentiatedGradient
 from fairlearn.reductions import DemographicParity
 from fairlearn.reductions import ErrorRate
-from fairlearn._input_validation import \
+from fairlearn.utils._input_validation import \
     (_LABELS_NOT_0_1_ERROR_MESSAGE)
 from .simple_learners import LeastSquaresBinaryClassifierLearner
 from .test_utilities import _get_data

diff --git a/test/unit/reductions/grid_search/test_grid_search_arguments.py b/test/unit/reductions/grid_search/test_grid_search_arguments.py
@@ -12,7 +12,7 @@
 from sklearn.pipeline import Pipeline
 from sklearn.preprocessing import StandardScaler
 
-from fairlearn._input_validation import \
+from fairlearn.utils._input_validation import \
     (_MESSAGE_Y_NONE,
      _LABELS_NOT_0_1_ERROR_MESSAGE)
 from fairlearn.reductions import GridSearch, DemographicParity, EqualizedOdds, BoundedGroupLoss, \