diff --git a/tensorflow/python/kernel_tests/batch_matmul_op_test.py b/tensorflow/python/kernel_tests/batch_matmul_op_test.py
index b68eaa123c5..dab4116ab9d 100644
--- a/tensorflow/python/kernel_tests/batch_matmul_op_test.py
+++ b/tensorflow/python/kernel_tests/batch_matmul_op_test.py
@@ -262,7 +262,8 @@ class BatchMatMulBenchmark(test.Benchmark):
 
 
 if __name__ == "__main__":
-  dtypes_to_test = [np.float16, np.float32, np.float64, np.int32, np.complex64, np.complex128]
+  dtypes_to_test = [np.float16, np.float32, np.float64, np.int32, 
+    np.complex64, np.complex128]
   for dtype_ in dtypes_to_test:
     for adjoint_a_ in False, True:
       for adjoint_b_ in False, True:
diff --git a/tensorflow/python/kernel_tests/eig_op_test.py b/tensorflow/python/kernel_tests/eig_op_test.py
index 74607c66dc2..4cfbcd21b49 100644
--- a/tensorflow/python/kernel_tests/eig_op_test.py
+++ b/tensorflow/python/kernel_tests/eig_op_test.py
@@ -183,7 +183,8 @@ def _GetEigTest(dtype_, shape_, compute_v_):
 
 
 if __name__ == "__main__":
-  dtypes_to_test = [dtypes_lib.float32, dtypes_lib.float64, dtypes_lib.complex64, dtypes_lib.complex128]
+  dtypes_to_test = [dtypes_lib.float32, dtypes_lib.float64, 
+    dtypes_lib.complex64, dtypes_lib.complex128]
   for compute_v in True, False:
     for dtype in dtypes_to_test:
       for size in 1, 2, 5, 10:
diff --git a/tensorflow/python/kernel_tests/linalg/linear_operator_adjoint_test.py b/tensorflow/python/kernel_tests/linalg/linear_operator_adjoint_test.py
index 409ab20985d..ad419ced5d1 100644
--- a/tensorflow/python/kernel_tests/linalg/linear_operator_adjoint_test.py
+++ b/tensorflow/python/kernel_tests/linalg/linear_operator_adjoint_test.py
@@ -199,7 +199,8 @@ class LinearOperatorAdjointTest(
 
   def test_solve_adjoint_complex_operator(self):
     if test.is_built_with_rocm():
-      self.skipTest("ROCm does not support BLAS solve operations for complex types")    
+      self.skipTest("ROCm does not support BLAS solve operations"
+        " for complex types")
     matrix1 = self.evaluate(linear_operator_test_util.random_tril_matrix(
         [4, 4], dtype=dtypes.complex128, force_well_conditioned=True) +
                             1j * linear_operator_test_util.random_tril_matrix(
diff --git a/tensorflow/python/kernel_tests/matmul_op_test.py b/tensorflow/python/kernel_tests/matmul_op_test.py
index dedfa58c3ed..cf562e094ed 100644
--- a/tensorflow/python/kernel_tests/matmul_op_test.py
+++ b/tensorflow/python/kernel_tests/matmul_op_test.py
@@ -226,7 +226,8 @@ class MatMulInfixOperatorTest(test_lib.TestCase):
 if __name__ == "__main__":
   sizes = [1, 3, 5]
   trans_options = [[False, False], [True, False], [False, True]]
-  dtypes_to_test = [np.int32, np.int64, np.float16, np.float32, np.float64, np.complex64, np.complex128]
+  dtypes_to_test = [np.int32, np.int64, np.float16, np.float32, np.float64, 
+    np.complex64, np.complex128]
   # TF2 does not support placeholders under eager so we skip it
   for use_static_shape in set([True, tf2.enabled()]):
     for dtype in dtypes_to_test:
diff --git a/tensorflow/python/kernel_tests/self_adjoint_eig_op_test.py b/tensorflow/python/kernel_tests/self_adjoint_eig_op_test.py
index ef64f7cf61b..73609a3c1cf 100644
--- a/tensorflow/python/kernel_tests/self_adjoint_eig_op_test.py
+++ b/tensorflow/python/kernel_tests/self_adjoint_eig_op_test.py
@@ -240,7 +240,8 @@ def _GetSelfAdjointEigGradTest(dtype_, shape_, compute_v_):
 
 
 if __name__ == "__main__":
-  dtypes_to_test = [dtypes_lib.float32, dtypes_lib.float64, dtypes_lib.complex64, dtypes_lib.complex128]
+  dtypes_to_test = [dtypes_lib.float32, dtypes_lib.float64, 
+    dtypes_lib.complex64, dtypes_lib.complex128]
   for compute_v in True, False:
     for dtype in dtypes_to_test:
       for size in 1, 2, 5, 10:
diff --git a/tensorflow/python/kernel_tests/tensordot_op_test.py b/tensorflow/python/kernel_tests/tensordot_op_test.py
index 3663a91281b..b63e3df6919 100644
--- a/tensorflow/python/kernel_tests/tensordot_op_test.py
+++ b/tensorflow/python/kernel_tests/tensordot_op_test.py
@@ -221,7 +221,8 @@ def _get_tensordot_tests(dtype_, rank_a_, rank_b_, num_dims_, dynamic_shape_):
 
 
 if __name__ == "__main__":
-  dtypes_to_test = [np.float16, np.float32, np.float64, np.complex64, np.complex128]
+  dtypes_to_test = [np.float16, np.float32, np.float64, 
+    np.complex64, np.complex128]
   for dtype in dtypes_to_test:
     for rank_a in 1, 2, 4, 5:
       for rank_b in 1, 2, 4, 5: