*
 * <p>All methods return serializable functions as long as they're given serializable parameters.
 *
 * <p>See the Guava User Guide article on <a
 * href="https://github.com/google/guava/wiki/FunctionalExplained">the use of {@code Function}</a>.
 *
 * @author Mike Bostock
 * @author Jared Levy
 * @since 2.0
 */
@GwtCompatible
@ElementTypesAreNonnullByDefault
public final class Functions {
  private Functions() {}

  /**

 *
 * <p>All methods return serializable functions as long as they're given serializable parameters.
 *
 * <p>See the Guava User Guide article on <a
 * href="https://github.com/google/guava/wiki/FunctionalExplained">the use of {@code Function}</a>.
 *
 * @author Mike Bostock
 * @author Jared Levy
 * @since 2.0
 */
@GwtCompatible
@ElementTypesAreNonnullByDefault
public final class Functions {
  private Functions() {}

  /**

        val daemonHeapMb = memoryHogMb * 5 + 400
        for (run in 1..runs) {
            println("Run number $run")
            myTask.writeText(myTask.readText().replace("runAction${run - 1}", "runAction$run"))
            buildWithDaemonHeapSize(daemonHeapMb, "myTask").apply {
                compilationCache {
                    assertCacheHits(run)
                }
                classLoadingCache {

  // a different TFE context for each thread of execution (for running graph
  // functions, and their send/recvs corountines).
  config.set_inter_op_parallelism_threads(1);

  TF_Buffer* ret = TF_NewBuffer();
  TF_CHECK_OK(MessageToBuffer(config, ret));
  return ret;
}

TF_Buffer* TF_CreateRunOptions(unsigned char enable_full_trace) {
  tensorflow::RunOptions options;
  if (enable_full_trace) {

    Function<? super Integer, Boolean> h = Functions.constant(Boolean.TRUE);
    Function<? super String, Integer> g = new HashCodeFunction();
    Function<Float, String> f = Functions.forMap(m, "F");

    Function<Float, Boolean> c1 = Functions.compose(Functions.compose(h, g), f);
    Function<Float, Boolean> c2 = Functions.compose(h, Functions.compose(g, f));

    // Might be nice (eventually) to have:

// TODO(sukritiramesh): Increase run iterations and move outside of the test
// suite.
TEST_F(LoaderTest, ResourceLeakTest) {
  SavedModelBundle bundle;
  SessionOptions session_options;
  RunOptions run_options;

  const string export_dir =
      io::JoinPath(testing::TensorFlowSrcRoot(), kTestDataSharded);
  for (int i = 0; i < 100; ++i) {
    TF_ASSERT_OK(LoadSavedModel(session_options, run_options, export_dir,

                Map.of("_default", List.of("QUERY1")),...

                         outputs);
  }

  Status Create(const RunOptions& run_options, const GraphDef& graph) override {
    return absl::UnimplementedError("Session::Create()");
  }
  Status Extend(const RunOptions& run_options, const GraphDef& graph) override {
    return absl::UnimplementedError("Session::Extend()");
  }
  Status Create(const RunOptions& run_options, GraphDef&& graph) override {

As dependencies will also be called by **FastAPI** (the same as your *path operation functions*), the same rules apply while defining your functions.

You can use `async def` or normal `def`.

And you can declare dependencies with `async def` inside of normal `def` *path operation functions*, or `def` dependencies inside of `async def` *path operation functions*, etc.

It doesn't matter. **FastAPI** will know what to do.

!!! note

std::unique_ptr<OperationPass<func::FuncOp>>
CreateInsertCustomAggregationOpsPass(
    const ::stablehlo::quantization::CalibrationOptions& calib_opts);

// Replaces composite functions with quantized composite functions. After this
// pass runs, functions in the given graph will be replaced with their quantized
// versions. By doing so, the quantization will be applied to the given input.