Fix black formatting

Author: abagusetty

dpnp/scipy/linalg/_decomp_lu.py

@@ -52,8 +52,9 @@
 )
 
 
-def lu(a, permute_l=False, overwrite_a=False, check_finite=True,
-       p_indices=False):
+def lu(
+    a, permute_l=False, overwrite_a=False, check_finite=True, p_indices=False
+):
     """
     Compute LU decomposition of a matrix with partial pivoting.
 

dpnp/scipy/linalg/_utils.py

@@ -137,7 +137,9 @@ def _get_real_dtype(res_type):
     """
 
     if dpnp.issubdtype(res_type, dpnp.complexfloating):
-        return dpnp.float32 if dpnp.dtype(res_type).itemsize <= 8 else dpnp.float64
+        return (
+            dpnp.float32 if dpnp.dtype(res_type).itemsize <= 8 else dpnp.float64
+        )
     return res_type
 
 
@@ -451,12 +453,12 @@ def _pivots_to_permutation(piv, m):
         j = piv[..., i : i + 1]
 
         # Gather the two values to be swapped.
-        val_i = perm[..., i : i + 1].copy()                   # slice (free)
-        val_j = dpnp.take_along_axis(perm, j, axis=-1)        # gather
+        val_i = perm[..., i : i + 1].copy()  # slice (free)
+        val_j = dpnp.take_along_axis(perm, j, axis=-1)  # gather
 
         # Perform the swap.
-        perm[..., i : i + 1] = val_j                           # slice assign
-        dpnp.put_along_axis(perm, j, val_i, axis=-1)           # scatter
+        perm[..., i : i + 1] = val_j  # slice assign
+        dpnp.put_along_axis(perm, j, val_i, axis=-1)  # scatter
 
     return perm
 

dpnp/tests/test_linalg.py

@@ -2743,7 +2743,9 @@ def test_p_is_permutation(self, dtype):
 
         assert_allclose(P_np.sum(axis=0), numpy.ones(5, dtype=P_np.dtype))
         assert_allclose(P_np.sum(axis=1), numpy.ones(5, dtype=P_np.dtype))
-        assert_allclose(P_np.T @ P_np, numpy.eye(5, dtype=P_np.dtype), atol=1e-15)
+        assert_allclose(
+            P_np.T @ P_np, numpy.eye(5, dtype=P_np.dtype), atol=1e-15
+        )
 
     @pytest.mark.parametrize("dtype", get_float_complex_dtypes())
     def test_modes_consistency(self, dtype):
@@ -2825,9 +2827,7 @@ def test_empty_p_indices(self, shape):
         ],
     )
     def test_strided(self, sl):
-        base = self._make_nonsingular_np(
-            (7, 7), dpnp.default_float_type(), "F"
-        )
+        base = self._make_nonsingular_np((7, 7), dpnp.default_float_type(), "F")
         a_np = base[sl]
         a_dp = dpnp.array(a_np)
 
@@ -2859,9 +2859,7 @@ def test_1d_input_raises(self):
     @pytest.mark.parametrize("bad", [numpy.inf, -numpy.inf, numpy.nan])
     def test_check_finite_raises(self, bad):
         a_dp = dpnp.array([[1.0, 2.0], [3.0, bad]], order="F")
-        assert_raises(
-            ValueError, dpnp.scipy.linalg.lu, a_dp, check_finite=True
-        )
+        assert_raises(ValueError, dpnp.scipy.linalg.lu, a_dp, check_finite=True)
 
     def test_check_finite_disabled(self):
         a_dp = dpnp.array([[1.0, numpy.nan], [3.0, 4.0]])
@@ -2976,8 +2974,12 @@ def test_modes_consistency_batched(self, dtype):
         a_np = self._make_nonsingular_nd_np((3, 4, 4), dtype, "F")
         a_dp = dpnp.array(a_np, order="F")
         A_cast = a_dp.astype(
-            dpnp.complex128 if dpnp.issubdtype(dtype, dpnp.complexfloating)
-            else dpnp.float64, copy=False
+            (
+                dpnp.complex128
+                if dpnp.issubdtype(dtype, dpnp.complexfloating)
+                else dpnp.float64
+            ),
+            copy=False,
         )
 
         P, L, U = dpnp.scipy.linalg.lu(a_dp)
@@ -3057,9 +3059,7 @@ def test_singular_matrix(self):
     def test_check_finite_raises(self):
         a = dpnp.ones((2, 3, 3), dtype=dpnp.default_float_type(), order="F")
         a[1, 0, 0] = dpnp.nan
-        assert_raises(
-            ValueError, dpnp.scipy.linalg.lu, a, check_finite=True
-        )
+        assert_raises(ValueError, dpnp.scipy.linalg.lu, a, check_finite=True)
 
 
 class TestMatrixPower:

dpnp/tests/test_sycl_queue.py

@@ -1665,6 +1665,7 @@ def test_lu_factor(self, data, device):
         for param in result:
             param_queue = param.sycl_queue
             assert_sycl_queue_equal(param_queue, a.sycl_queue)
+
     def test_lu(self, data, device):
         a = dpnp.array(data, device=device)
         result = dpnp.scipy.linalg.lu(a)

dpnp/tests/test_usm_type.py

@@ -1538,6 +1538,7 @@ def test_lu(self, data, usm_type):
         assert a.usm_type == usm_type
         for param in result:
             assert param.usm_type == a.usm_type
+
     def test_lu_factor(self, data, usm_type):
         a = dpnp.array(data, usm_type=usm_type)
         result = dpnp.scipy.linalg.lu_factor(a)