scikit-learn
diff --git a/‎doc/whats_new/v1.0.rst
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+6-1Lines changed: 6 additions & 1 deletion b/‎doc/whats_new/v1.0.rst
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+6-1Lines changed: 6 additions & 1 deletion
diff --git a/‎sklearn/decomposition/_dict_learning.py
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+3-1Lines changed: 3 additions & 1 deletion b/‎sklearn/decomposition/_dict_learning.py
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+3-1Lines changed: 3 additions & 1 deletion
@@ -65,13 +65,18 @@ Changelog
 - |API| In :class:`decomposition.DictionaryLearning`,
   :class:`decomposition.MiniBatchDictionaryLearning`,
   :func:`dict_learning` and :func:`dict_learning_online`,
-  `transform_alpha` will be equal to `alpha` instead of 1.0 by default 
+  `transform_alpha` will be equal to `alpha` instead of 1.0 by default
   starting from version 1.2
   :pr:`19159` by :user:`Benoît Malézieux <bmalezieux>`.
 
 - |Fix| Fixes incorrect multiple data-conversion warnings when clustering
   boolean data. :pr:`19046` by :user:`Surya Prakash <jdsurya>`.
 
+- |Fix| Fixed :func:`dict_learning`, used by :class:`DictionaryLearning`, to
+  ensure determinism of the output. Achieved by flipping signs of the SVD
+  output which is used to initialize the code.
+  :pr:`18433` by :user:`Bruno Charron <brcharron>`.
+
 :mod:`sklearn.ensemble`
 .......................
 
 
@@ -18,7 +18,7 @@
 from ..utils import deprecated
 from ..utils import (check_array, check_random_state, gen_even_slices,
                      gen_batches)
-from ..utils.extmath import randomized_svd, row_norms
+from ..utils.extmath import randomized_svd, row_norms, svd_flip
 from ..utils.validation import check_is_fitted, _deprecate_positional_args
 from ..utils.fixes import delayed
 from ..linear_model import Lasso, orthogonal_mp_gram, LassoLars, Lars
@@ -567,6 +567,8 @@ def dict_learning(X, n_components, *, alpha, max_iter=100, tol=1e-8,
         dictionary = dict_init
     else:
         code, S, dictionary = linalg.svd(X, full_matrices=False)
+        # flip the initial code's sign to enforce deterministic output
+        code, dictionary = svd_flip(code, dictionary)
         dictionary = S[:, np.newaxis] * dictionary
     r = len(dictionary)
     if n_components <= r:  # True even if n_components=None