DOC Fix documentation example sparsefuncs_fast (scikit-learn#29526) (scikit-learn#29527)

Author: ThomAub

sklearn/utils/sparsefuncs_fast.pyx

@@ -489,7 +489,11 @@ def inplace_csr_row_normalize_l1(X):
     --------
     >>> from scipy.sparse import csr_matrix
     >>> from sklearn.utils.sparsefuncs_fast import inplace_csr_row_normalize_l1
-    >>> X = csr_matrix(([1.0, 2.0, 3.0], [0, 2, 3], [0, 3, 4]), shape=(3, 4))
+    >>> import numpy as np
+    >>> indptr = np.array([0, 2, 3, 4])
+    >>> indices = np.array([0, 1, 2, 3])
+    >>> data = np.array([1.0, 2.0, 3.0, 4.0])
+    >>> X = csr_matrix((data, indices, indptr), shape=(3, 4))
     >>> X.toarray()
     array([[1., 2., 0., 0.],
            [0., 0., 3., 0.],
@@ -547,7 +551,11 @@ def inplace_csr_row_normalize_l2(X):
     --------
     >>> from scipy.sparse import csr_matrix
     >>> from sklearn.utils.sparsefuncs_fast import inplace_csr_row_normalize_l2
-    >>> X = csr_matrix(([1.0, 2.0, 3.0], [0, 2, 3], [0, 3, 4]), shape=(3, 4))
+    >>> import numpy as np
+    >>> indptr = np.array([0, 2, 3, 4])
+    >>> indices = np.array([0, 1, 2, 3])
+    >>> data = np.array([1.0, 2.0, 3.0, 4.0])
+    >>> X = csr_matrix((data, indices, indptr), shape=(3, 4))
     >>> X.toarray()
     array([[1., 2., 0., 0.],
            [0., 0., 3., 0.],