Fix code format following ruff update

keras/src/backend/openvino/core.py

@@ -242,9 +242,9 @@ def __getitem__(self, indices):
     def __len__(self):
         ov_output = self.output
         ov_shape = ov_output.get_partial_shape()
-        assert (
-            ov_shape.rank.is_static and ov_shape.rank.get_length() > 0
-        ), "rank must be static and greater than zero"
+        assert ov_shape.rank.is_static and ov_shape.rank.get_length() > 0, (
+            "rank must be static and greater than zero"
+        )
         assert ov_shape[0].is_static, "the first dimension must be static"
         return ov_shape[0].get_length()
 
@@ -425,10 +425,10 @@ def convert_to_numpy(x):
             x = x.value
         else:
             return x.value.data
-    assert isinstance(
-        x, OpenVINOKerasTensor
-    ), "unsupported type {} for `convert_to_numpy` in openvino backend".format(
-        type(x)
+    assert isinstance(x, OpenVINOKerasTensor), (
+        "unsupported type {} for `convert_to_numpy` in openvino backend".format(
+            type(x)
+        )
     )
     try:
         ov_result = x.output

keras/src/backend/openvino/nn.py

@@ -325,9 +325,9 @@ def depthwise_conv(
     data_format = backend.standardize_data_format(data_format)
     num_spatial_dims = inputs.get_partial_shape().rank.get_length() - 2
 
-    assert (
-        data_format == "channels_last"
-    ), "`depthwise_conv` is supported only for channels_last data_format"
+    assert data_format == "channels_last", (
+        "`depthwise_conv` is supported only for channels_last data_format"
+    )
 
     strides = _adjust_strides_dilation(strides, num_spatial_dims)
     dilation_rate = _adjust_strides_dilation(dilation_rate, num_spatial_dims)

keras/src/backend/openvino/numpy.py

@@ -81,9 +81,9 @@ def mean(x, axis=None, keepdims=False):
 
 
 def max(x, axis=None, keepdims=False, initial=None):
-    assert (
-        initial is None
-    ), "`max` with not None initial is not supported by openvino backend"
+    assert initial is None, (
+        "`max` with not None initial is not supported by openvino backend"
+    )
     x = get_ov_output(x)
     reduce_axis = ov_opset.constant(axis, Type.i32).output(0)
     return OpenVINOKerasTensor(
@@ -260,9 +260,9 @@ def bincount(x, weights=None, minlength=0, sparse=False):
 
 
 def broadcast_to(x, shape):
-    assert isinstance(
-        shape, (tuple, list)
-    ), "`broadcast_to` is supported only for tuple and list `shape`"
+    assert isinstance(shape, (tuple, list)), (
+        "`broadcast_to` is supported only for tuple and list `shape`"
+    )
     target_shape = ov_opset.constant(list(shape), Type.i32).output(0)
     x = get_ov_output(x)
     return OpenVINOKerasTensor(ov_opset.broadcast(x, target_shape).output(0))

keras/src/ops/numpy_test.py

@@ -24,9 +24,9 @@ def test_basic(self):
         array = np.array([[1, 2], [3, 4]])
         rotated = knp.rot90(array)
         expected = np.array([[2, 4], [1, 3]])
-        assert np.array_equal(
-            rotated, expected
-        ), f"Failed basic 2D test: {rotated}"
+        assert np.array_equal(rotated, expected), (
+            f"Failed basic 2D test: {rotated}"
+        )
 
     def test_multiple_k(self):
         array = np.array([[1, 2], [3, 4]])
@@ -50,9 +50,9 @@ def test_axes(self):
         array = np.arange(8).reshape((2, 2, 2))
         rotated = knp.rot90(array, k=1, axes=(1, 2))
         expected = np.array([[[1, 3], [0, 2]], [[5, 7], [4, 6]]])
-        assert np.array_equal(
-            rotated, expected
-        ), f"Failed custom axes test: {rotated}"
+        assert np.array_equal(rotated, expected), (
+            f"Failed custom axes test: {rotated}"
+        )
 
     def test_single_image(self):
         array = np.random.random((4, 4, 3))
@@ -83,9 +83,9 @@ def test_invalid_rank(self):
         try:
             knp.rot90(array)
         except ValueError as e:
-            assert "Input array must have at least 2 dimensions." in str(
-                e
-            ), f"Failed invalid rank test: {e}"
+            assert "Input array must have at least 2 dimensions." in str(e), (
+                f"Failed invalid rank test: {e}"
+            )
         else:
             raise AssertionError("Failed to raise error for invalid input")