value = schema["$ref"]
            if isinstance(value, str):
                ref_name = schema["$ref"].split("/")[-1]
                if ref_name in old_name_to_new_name_map:
                    new_name = old_name_to_new_name_map[ref_name]
                    new_schema["$ref"] = REF_TEMPLATE.format(model=new_name)
            continue
        if isinstance(value, dict):
            new_schema[key] = _replace_refs(

    String oldName = Thread.currentThread().getName();
    Supplier<String> newName = Suppliers.ofInstance("MyCrazyThreadName");
    Callable<@Nullable Void> callable =
        new Callable<@Nullable Void>() {
          @Override
          public @Nullable Void call() throws Exception {
            assertEquals(Thread.currentThread().getName(), newName.get());
            return null;
          }
        };

func (m Migrator) RenameColumn(value interface{}, oldName, newName string) error {
	return m.RunWithValue(value, func(stmt *gorm.Statement) error {
		if stmt.Schema != nil {
			if field := stmt.Schema.LookUpField(oldName); field != nil {
				oldName = field.DBName
			}

			if field := stmt.Schema.LookUpField(newName); field != nil {
				newName = field.DBName
			}
		}

		t.Fatalf("prepare user failed: %v", err)
	}

	// update with Set after chain
	newName := "GenericsSetUpdate_After"
	newAge := uint(31)
	rows, err := gorm.G[User](DB).
		Where("id = ?", u.ID).
		Set(
			clause.Assignment{Column: clause.Column{Name: "name"}, Value: newName},
			clause.Assignment{Column: clause.Column{Name: "age"}, Value: newAge},
		).
		Update(ctx)
	if err != nil {

  // executing the following code.
  for (int i = first_new_node_id; i < parent->graph.num_node_ids(); ++i) {
    Node* new_node = parent->graph.FindNodeId(i);
    if (new_node == nullptr) continue;
    parent->name_map[new_node->name()] = new_node;
  }

  // Populate 'outputs'.
  DCHECK_LE(loop_outputs.size(), num_loop_vars);
  for (int i = 0; i < loop_outputs.size(); ++i) {

  using tensorflow::shape_inference::ShapeHandle;

  const int num_inputs = input_shapes->num_items;
  NodeDef node_def;
  tensorflow::ImmediateExecutionOperation* op = tensorflow::unwrap(tfe_op);
  node_def.set_name(op->Name());
  node_def.set_op(op->Name());
  for (int i = 0; i < num_inputs; ++i) {
    node_def.add_input("dummy_input");
  }
  OperationFromInterface(op)->Attrs().FillAttrValueMap(node_def.mutable_attr());

                        + "    <loc>http://www.example.com/news/article.html</loc>\n" + "    <news:news>\n" + "      <news:publication>\n"
                        + "        <news:name>Example Times</news:name>\n" + "        <news:language>en</news:language>\n"
                        + "      </news:publication>\n" + "      <news:publication_date>2025-01-01</news:publication_date>\n"

        private static final String NEWS_NEWS_ELEMENT = "news:news";

        private static final String NEWS_PUBLICATION_ELEMENT = "news:publication";

        private static final String NEWS_NAME_ELEMENT = "news:name";

        private static final String NEWS_LANGUAGE_ELEMENT = "news:language";

        private static final String NEWS_PUBLICATION_DATE_ELEMENT = "news:publication_date";

from starlette.exceptions import HTTPException
from starlette.requests import Request
from starlette.responses import JSONResponse, Response
from starlette.routing import (
    BaseRoute,
    Match,
    compile_path,
    get_name,
)
from starlette.routing import Mount as Mount  # noqa
from starlette.types import AppType, ASGIApp, Lifespan, Receive, Scope, Send
from starlette.websockets import WebSocket
from typing_extensions import deprecated

  if (TF_TensorDefaultAlignment() > 0) {
    EXPECT_FALSE(TF_TensorIsAligned(a));
  }
  TF_DeleteTensor(a);
}

TEST(CAPI, MessageBufferConversion) {
  NodeDef node_in, node_out;
  node_in.set_name("Test name");
  node_in.set_op("Test op");

  TF_Buffer* buffer = TF_NewBuffer();
  TF_CHECK_OK(MessageToBuffer(node_in, buffer));
  TF_CHECK_OK(BufferToMessage(buffer, &node_out));
  TF_DeleteBuffer(buffer);