try:
        yield session
    finally:
        session.open = False


def dep_session() -> Any:
    with acquire_session() as s:
        yield s


def broken_dep_session() -> Any:
    with acquire_session() as s:
        s.open = False
        yield s


SessionDep = Annotated[Session, Depends(dep_session)]
BrokenSessionDep = Annotated[Session, Depends(broken_dep_session)]

app = FastAPI()

// API for driving Graph execution.

typedef struct TF_Session TF_Session;

// Return a new execution session with the associated graph, or NULL on
// error. Does not take ownership of any input parameters.
//
// *`graph` must be a valid graph (not deleted or nullptr). `graph` will be
// kept alive for the lifetime of the returned TF_Session. New nodes can still
// be added to `graph` after this call.

#endif  // defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
}

// TF_Session functions ----------------------------------------------

TF_Session::TF_Session(tensorflow::Session* s, TF_Graph* g)
    : session(s), graph(g), last_num_graph_nodes(0), extend_before_run(true) {}

TF_Session* TF_NewSession(TF_Graph* graph, const TF_SessionOptions* opt,
                          TF_Status* status) {

// empty, this call is blocked.
//
// Tensors are enqueued via the corresponding TF enqueue op.
// TODO(hongm): Add support for `timeout_ms`.
TF_CAPI_EXPORT extern TF_Tensor* TF_DequeueNamedTensor(TF_Session* session,
                                                       int tensor_id,
                                                       TF_Status* status);

        request.lifecycleBindingsInjector(lifecycleBindingsInjector::injectLifecycleBindings);
        ModelBuilder.ModelBuilderSession mbSession =
                iSession.getData().get(SessionData.key(ModelBuilder.ModelBuilderSession.class));
        return mbSession.build(request.build());
    }

    static Model transformNonPom(Model model, MavenProject project) {

    if (!status->status.ok()) return {};
    ret.push_back(UniqueFuncPtr(func, TF_DeleteFunction));
  }
  return ret;
}

TF_Tensor* TF_DequeueNamedTensor(TF_Session* session, int tensor_id,
                                 TF_Status* status) {
  assert(session);
  {
    tensorflow::mutex_lock c(session->graph->mu);
    VLOG(1) << "Dequeuing named tensor with id " << tensor_id

     * but an implemantation that encorporates the transport header(for
     * efficiency) might use a different initial bufferIndex. For example,
     * to eliminate copying data when writing NbtSession data one might
     * manage that 4 byte header specifically and therefore the initial
     * bufferIndex, and thus headerStart, would be 4).(NOTE: If one where

      << "'" << s << "' does not contain '" << expected << "'";
}

// Returns the GPU device name if there is one (with arbitrary tie breaking if
// there are more than one), or "" otherwise.
std::string GPUDeviceName(TF_Session* session) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);
  TF_Status* s = status.get();
  std::unique_ptr<TF_DeviceList, decltype(&TF_DeleteDeviceList)> list(

// TFE_Context must outlive all tensor handles created using it. In other
// words, TFE_DeleteContext() must be called after all tensor handles have
// been deleted (with TFE_DeleteTensorHandle).
//
// TODO(ashankar): Merge with TF_Session?
typedef struct TFE_Context TFE_Context;

TF_CAPI_EXPORT extern TFE_Context* TFE_NewContext(
    const TFE_ContextOptions* opts, TF_Status* status);
TF_CAPI_EXPORT extern void TFE_DeleteContext(TFE_Context* ctx);

  TF_SessionOptions* opts = TF_NewSessionOptions();
  TF_EnableXLACompilation(opts, use_XLA);
  session_ = TF_NewSession(graph, opts, s);
  TF_DeleteSessionOptions(opts);
}

CSession::CSession(TF_Session* session) : session_(session) {}

CSession::~CSession() {
  TF_Status* s = TF_NewStatus();
  CloseAndDelete(s);
  EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_DeleteStatus(s);
}