FIX allow ndim>2 in shuffle

Fixes scikit-learn#3694.

Author: wlamond

sklearn/utils/__init__.py

@@ -242,8 +242,8 @@ def resample(*arrays, **options):
             max_n_samples, n_samples))
 
     check_consistent_length(*arrays)
-    arrays = [check_array(x, accept_sparse='csr', ensure_2d=False)
-              for x in arrays]
+    arrays = [check_array(x, accept_sparse='csr', ensure_2d=False,
+                          allow_nd=True) for x in arrays]
 
     if replace:
         indices = random_state.randint(0, n_samples, size=(max_n_samples,))

sklearn/utils/tests/test_utils.py

@@ -14,6 +14,7 @@
 from sklearn.utils import safe_mask
 from sklearn.utils import column_or_1d
 from sklearn.utils import safe_indexing
+from sklearn.utils import shuffle
 from sklearn.utils.extmath import pinvh
 from sklearn.utils.mocking import MockDataFrame
 
@@ -175,3 +176,8 @@ def test_safe_indexing_mock_pandas():
     X_df_indexed = safe_indexing(X_df, inds)
     X_indexed = safe_indexing(X_df, inds)
     assert_array_equal(np.array(X_df_indexed), X_indexed)
+
+
+def test_shuffle_on_ndim_equals_three():
+    A = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])  # A.shape = (2,2,2)
+    shuffle(A)  # shouldn't raise a ValueError for dim = 3