// that work on TF dialect and before inliner so that the function calls in
  // body and cond are inlined for optimization.
  pass_manager->addPass(mlir::TFL::CreateLegalizeTFWhilePass());

  // Add function inlining pass. Both TF and TFLite dialects are opted into
  // function inliner interface.
  pass_manager->addPass(mlir::createInlinerPass());

		}
	}

	{
		a := 2
		if r := func(x int) int { // ERROR "can inline main.func28"
			b := 3
			return func(y int) int { // ERROR "can inline main.func28.1" "can inline main.main.func28.func35"
				c := 5
				func(z int) { // ERROR "can inline main.func28.1.1" "can inline main.func28.main.func28.1.2" "can inline main.main.func28.func35.1" "can inline main.main.func28.main.main.func28.func35.func37"
					a = a * x
					b = b * y

	// from another package is imported and inlined.
	Dcl     []*Name
	HaveDcl bool // whether we've loaded Dcl

	// Function properties, encoded as a string (these are used for
	// making inlining decisions). See cmd/compile/internal/inline/inlheur.
	Properties string

	// CanDelayResults reports whether it's safe for the inliner to delay
	// initializing the result parameters until immediately before the

    const LayoutOptimizationPipelineOptions& options);

struct StandardPipelineOptions
    : public PassPipelineOptions<StandardPipelineOptions> {
  Option<bool> enable_inliner{*this, "enable-inliner",
                              llvm::cl::desc("Enable inliner."),
                              llvm::cl::init(false)};
  Option<bool> form_clusters{*this, "form-clusters",
                             llvm::cl::desc("Enable Cluster Formation pass."),

    //     post inlining, the function will be dead and eliminated from the IR.
    //     So there won't be any code duplication.
    // plus the function caller op can be replaced by inlined ops.
    return !wouldBeCloned || TensorFlowDialect::CanDuplicate(op);
  }

  //===--------------------------------------------------------------------===//
  // Transformation Hooks

	// This function is designed to allow the caller to control the lifetime
	// of the returned *UDPAddr and thereby prevent an allocation.
	// See https://blog.filippo.io/efficient-go-apis-with-the-inliner/.
	// The real work is done by readFromUDP, below.
	return c.readFromUDP(b, &UDPAddr{})
}

// readFromUDP implements ReadFromUDP.
func (c *UDPConn) readFromUDP(b []byte, addr *UDPAddr) (int, *UDPAddr, error) {

		},
		// function, inlined
		{
			func(buf []byte) int { return testTracebackGenericFnInlined[int](buf) },
			"testTracebackGenericFnInlined[...](",
		},
		// method, not inlined
		{
			x.M,
			"testTracebackGenericTyp[...].M(",
		},
		// method, inlined
		{
			func(buf []byte) int { return x.Inlined(buf) },
			"testTracebackGenericTyp[...].Inlined(",
		},
	}
	var buf [1000]byte

				name, ok := originDIE.Val(dwarf.AttrName).(string)
				if !ok {
					t.Fatalf("no name attr for inlined subroutine at offset %v", child.Offset)
				}
				if name != "main.inlined" {
					t.Fatalf("expected inlined routine %s got %s", "main.cand", name)
				}

				// Verify that the call_file attribute for the inlined
				// instance is ok. In this case it should match the file

      mlir::mhlo::CreateTFXLADeviceSpecificTransformsPass(device_type));

  // Note that the region-based control-flow produced here still contains
  // function call ops which get inlined by the subsequent inliner pass.
  pm.addPass(mlir::TF::CreateTFFunctionalControlFlowToRegions());
  pm.addPass(mlir::createInlinerPass());
  pm.addNestedPass<mlir::func::FuncOp>(
      mlir::TF::CreateDropWhileShapeInvariantPass());

type InlCall struct {
	// index into ctx.InlTree describing the call inlined here
	InlIndex int

	// Position of the inlined call site.
	CallPos src.Pos

	// Dwarf abstract subroutine symbol (really *obj.LSym).
	AbsFunSym Sym

	// Indices of child inlines within Calls array above.
	Children []int

	// entries in this list are PAUTO's created by the inliner to
	// capture the promoted formals and locals of the inlined callee.