chore: fixing lint and formatting (#304)

Author: fracarfer5

src/holisticai/bias/metrics/_classification.py

@@ -4,6 +4,10 @@
 import numpy as np
 import pandas as pd
 
+# Efficacy metrics
+from sklearn.metrics import accuracy_score, confusion_matrix, roc_auc_score
+from sklearn.neighbors import NearestNeighbors
+
 # utils
 from holisticai.utils._validation import (
     _array_like_to_numpy,
@@ -13,10 +17,6 @@
     _regression_checks,
 )
 
-# Efficacy metrics
-from sklearn.metrics import accuracy_score, confusion_matrix, roc_auc_score
-from sklearn.neighbors import NearestNeighbors
-
 
 def _group_success_rate(g, y):
     """Group success rate.

src/holisticai/bias/metrics/_clustering.py

@@ -1,7 +1,5 @@
 import numpy as np
 import pandas as pd
-from holisticai.utils._recommender_tools import entropy
-from holisticai.utils._validation import _clustering_checks
 
 # sklearn imports
 from sklearn.metrics import (
@@ -10,6 +8,9 @@
     silhouette_samples,
 )
 
+from holisticai.utils._recommender_tools import entropy
+from holisticai.utils._validation import _clustering_checks
+
 
 def cluster_balance(group_a, group_b, y_pred):
     """Cluster Balance

src/holisticai/bias/metrics/_recommender.py

@@ -2,6 +2,9 @@
 import numpy as np
 import pandas as pd
 
+# sklearn imports
+from sklearn.metrics import mean_absolute_error
+
 # utils
 from holisticai.utils import mat_to_binary, normalize_tensor
 
@@ -16,9 +19,6 @@
 )
 from holisticai.utils._validation import _recommender_checks
 
-# sklearn imports
-from sklearn.metrics import mean_absolute_error
-
 
 def aggregate_diversity(mat_pred, top=None, thresh=0.5, normalize=False):
     r"""Aggregate Diversity

src/holisticai/bias/mitigation/inprocessing/adversarial_debiasing/transformer.py

@@ -6,6 +6,7 @@
 import jax.numpy as jnp
 import numpy as np
 import pandas as pd
+
 from holisticai.bias.mitigation.inprocessing.adversarial_debiasing.models import (
     ADModel,
     AdversarialModel,

src/holisticai/bias/mitigation/inprocessing/commons/_moments_utils.py

@@ -2,6 +2,7 @@
 
 import numpy as np
 import pandas as pd
+
 from holisticai.bias.mitigation.inprocessing.commons._conventions import _EVENT, _GROUP_ID, _LABEL, _SIGNED
 
 

src/holisticai/bias/mitigation/inprocessing/commons/classification/_constraints.py

@@ -2,6 +2,7 @@
 
 import numpy as np
 import pandas as pd
+
 from holisticai.bias.mitigation.inprocessing.commons._conventions import (
     _ALL,
     _EVENT,

src/holisticai/bias/mitigation/inprocessing/commons/classification/_objectives.py

@@ -1,5 +1,6 @@
 import numpy as np
 import pandas as pd
+
 from holisticai.bias.mitigation.inprocessing.commons._conventions import _ALL, _LABEL
 from holisticai.bias.mitigation.inprocessing.commons._moments_utils import BaseMoment
 

src/holisticai/bias/mitigation/inprocessing/commons/regression/_constraints.py

@@ -1,5 +1,6 @@
 import numpy as np
 import pandas as pd
+
 from holisticai.bias.mitigation.inprocessing.commons._conventions import (
     _ALL,
     _EVENT,

src/holisticai/bias/mitigation/inprocessing/exponentiated_gradient/_lagrangian.py

@@ -1,9 +1,10 @@
 import numpy as np
 import pandas as pd
 import scipy.optimize as opt
-from holisticai.bias.mitigation.inprocessing.commons._conventions import PRECISION
 from sklearn import clone
 
+from holisticai.bias.mitigation.inprocessing.commons._conventions import PRECISION
+
 
 class Lagrangian:
     """Operations related to the Lagrangian"""

src/holisticai/bias/mitigation/inprocessing/exponentiated_gradient/algorithm.py

@@ -4,6 +4,8 @@
 
 import numpy as np
 import pandas as pd
+from sklearn.utils import check_random_state
+
 from holisticai.bias.mitigation.inprocessing.commons._conventions import (
     ACCURACY_MUL,
     MIN_ITER,
@@ -14,7 +16,6 @@
     SHRINK_REGRET,
 )
 from holisticai.bias.mitigation.inprocessing.exponentiated_gradient._lagrangian import Lagrangian
-from sklearn.utils import check_random_state
 
 
 class ExponentiatedGradientAlgorithm: