Replace tensorflow::Status::OK() with tensorflow::OkStatus().

PiperOrigin-RevId: 473798088

Author: jblespiau

research/carls/base/status_helper_test.cc

@@ -41,7 +41,7 @@ TEST(ProtoFactoryTest, ToAbslStatus_Grpc) {
 }
 
 TEST(ProtoFactoryTest, ToAbslStatus_TensorFlow) {
-  EXPECT_EQ(absl::OkStatus(), carls::ToAbslStatus(tensorflow::Status::OK()));
+  EXPECT_EQ(absl::OkStatus(), carls::ToAbslStatus(tensorflow::OkStatus()));
 
   auto tf_status =
       tensorflow::Status(tensorflow::error::INVALID_ARGUMENT, "Error.");

research/carls/kernels/dynamic_embedding_manager_resource.cc

@@ -95,7 +95,7 @@ class DynamicEmbeddingManagerResourceOp
       return Status(tensorflow::error::FAILED_PRECONDITION,
                     "DynamicEmbeddingManager is NULL.");
     }
-    return Status::OK();
+    return tensorflow::OkStatus();
   }
 
   DynamicEmbeddingConfig config_;

research/carls/kernels/dynamic_embedding_ops.cc

@@ -64,7 +64,7 @@ Status SetInputShape(InferenceContext* c) {
                   DimensionOrConstant(embedding_dimension));
     c->set_output(0, output_shape);
   }
-  return Status::OK();
+  return tensorflow::OkStatus();
 }
 
 }  // namespace

research/carls/kernels/dynamic_memory_ops.cc

@@ -56,7 +56,7 @@ REGISTER_OP("DynamicGaussianMemoryLookup")
         }
         c->set_output(2, c->MakeShape(dims));
       }
-      return Status::OK();
+      return tensorflow::OkStatus();
     })
     .Doc(R"doc(
 A Gaussian memory assumes the input pattern can be represented by a number of

research/carls/testing/test_helper_test.cc

@@ -58,13 +58,13 @@ TEST(TestHelperTest, GrpcStatusChecks) {
 }
 
 TEST(TestHelperTest, TensoFlowStatusChecks) {
-  EXPECT_OK(tensorflow::Status::OK());
+  EXPECT_OK(tensorflow::OkStatus());
   EXPECT_NOT_OK(
       tensorflow::Status(tensorflow::error::INVALID_ARGUMENT, "First error."));
   EXPECT_ERROR_EQ(
       tensorflow::Status(tensorflow::error::INVALID_ARGUMENT, "First error."),
       "First error.");
-  ASSERT_OK(tensorflow::Status::OK());
+  ASSERT_OK(tensorflow::OkStatus());
   ASSERT_ERROR_EQ(
       tensorflow::Status(tensorflow::error::INVALID_ARGUMENT, "Second error."),
       "Second error.");