Ensure determinism of SVD output in dict_learning

scikit-learn · Sep 20, 2020 · 759593e · 759593e
1 parent 8b68ea1
commit 759593e
Showing 1 changed file with 2 additions and 1 deletion.
diff --git a/sklearn/decomposition/_dict_learning.py b/sklearn/decomposition/_dict_learning.py
@@ -17,7 +17,7 @@
 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 ..linear_model import Lasso, orthogonal_mp_gram, LassoLars, Lars
 
@@ -563,6 +563,7 @@ 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)
+        code, dictionary = svd_flip(code, dictionary)
         dictionary = S[:, np.newaxis] * dictionary
     r = len(dictionary)
     if n_components <= r:  # True even if n_components=None