From e15df5dda638c13b42b85bdb6970589376a43bb4 Mon Sep 17 00:00:00 2001
From: Yannick DAYER <yannick.dayer@idiap.ch>
Date: Tue, 3 May 2022 20:14:15 +0200
Subject: [PATCH] Add super().__init__() to classes
---
bob/learn/em/gmm.py | 4 +++-
bob/learn/em/kmeans.py | 3 +++
bob/learn/em/wccn.py | 3 ++-
bob/learn/em/whitening.py | 3 ++-
4 files changed, 10 insertions(+), 3 deletions(-)
diff --git a/bob/learn/em/gmm.py b/bob/learn/em/gmm.py
index 1a439e1..d9ae87b 100644
--- a/bob/learn/em/gmm.py
+++ b/bob/learn/em/gmm.py
@@ -183,7 +183,9 @@ class GMMStats:
Second order statistic
"""
- def __init__(self, n_gaussians: int, n_features: int) -> None:
+ def __init__(self, n_gaussians: int, n_features: int, **kwargs) -> None:
+ super().__init__(**kwargs)
+
self.n_gaussians = n_gaussians
self.n_features = n_features
self.log_likelihood = 0
diff --git a/bob/learn/em/kmeans.py b/bob/learn/em/kmeans.py
index 61af76e..6cd29e4 100644
--- a/bob/learn/em/kmeans.py
+++ b/bob/learn/em/kmeans.py
@@ -202,6 +202,7 @@ class KMeansMachine(BaseEstimator):
random_state: Union[int, np.random.RandomState] = 0,
init_max_iter: Union[int, None] = 5,
oversampling_factor: float = 2,
+ **kwargs,
) -> None:
"""
Parameters
@@ -219,6 +220,8 @@ class KMeansMachine(BaseEstimator):
The maximum number of iterations for the initialization part.
"""
+ super().__init__(**kwargs)
+
if n_clusters < 1:
raise ValueError("The Number of cluster should be greater thant 0.")
self.n_clusters = n_clusters
diff --git a/bob/learn/em/wccn.py b/bob/learn/em/wccn.py
index 47d5b80..32a4e80 100644
--- a/bob/learn/em/wccn.py
+++ b/bob/learn/em/wccn.py
@@ -34,7 +34,8 @@ class WCCN(TransformerMixin, BaseEstimator):
"""
- def __init__(self, pinv=False):
+ def __init__(self, pinv=False, **kwargs):
+ super().__init__(**kwargs)
self.pinv = pinv
def fit(self, X, y):
diff --git a/bob/learn/em/whitening.py b/bob/learn/em/whitening.py
index bf81a36..4b78da8 100644
--- a/bob/learn/em/whitening.py
+++ b/bob/learn/em/whitening.py
@@ -41,7 +41,8 @@ class Whitening(TransformerMixin, BaseEstimator):
"""
- def __init__(self, pinv: bool = False):
+ def __init__(self, pinv: bool = False, **kwargs):
+ super().__init__(**kwargs)
self.pinv = pinv
def fit(self, X, y=None):
--
GitLab