}
	}

	return
}

var cgoPrefixes = [...]string{
	"_Ciconst_",
	"_Cfconst_",
	"_Csconst_",
	"_Ctype_",
	"_Cvar_", // actually a pointer to the var
	"_Cfpvar_fp_",
	"_Cfunc_",
	"_Cmacro_", // function to evaluate the expanded expression
}

func (check *Checker) selector(x *operand, e *syntax.SelectorExpr, def *TypeName, wantType bool) {

		}
	}

	return
}

var cgoPrefixes = [...]string{
	"_Ciconst_",
	"_Cfconst_",
	"_Csconst_",
	"_Ctype_",
	"_Cvar_", // actually a pointer to the var
	"_Cfpvar_fp_",
	"_Cfunc_",
	"_Cmacro_", // function to evaluate the expanded expression
}

func (check *Checker) selector(x *operand, e *ast.SelectorExpr, def *TypeName, wantType bool) {

	var goname string
	switch fun := call.Call.Fun.(type) {
	case *ast.SelectorExpr:
		goname = fun.Sel.Name
	case *ast.Ident:
		goname = strings.TrimPrefix(fun.Name, "_C2func_")
		goname = strings.TrimPrefix(goname, "_Cfunc_")
	}
	if goname == "" || goname == "malloc" {
		return "", false
	}
	name := f.Name[goname]
	if name == nil || name.Kind != "func" {
		// Probably a type conversion.

void ConvertNMSPaddedFunc::RewriteFunc() {
  func_->setAttr(kTFImplements,
                 StringAttr::get(func_.getContext(), kTfNMSPadded));
  Value boxes = func_.getArgument(0);
  Value scores = func_.getArgument(1);
  Value max_output_size = func_.getArgument(2);
  Value iou_threshold = func_.getArgument(3);
  Value score_threshold = func_.getArgument(4);
  auto output_type0 = func_.getFunctionType().getResult(0);

LogicalResult ConvertDenseImageWarpFunc::RewriteFunc() {
  func_.eraseBody();
  func_.addEntryBlock();
  func_->setAttr(kTFImplements,
                 StringAttr::get(func_.getContext(), kImageWarping));

  OpBuilder builder(func_.getBody());
  auto op = builder.create<CustomOp>(func_.getLoc(),
                                     func_.getFunctionType().getResults(),
                                     func_.getArguments(), kImageWarping,

  explicit ConvertEmbeddedLookupFunc(func::FuncOp func) : func_(func) {}

  void RewriteFunc() {
    func_->setAttr(kTFImplements,
                   StringAttr::get(func_.getContext(), "embedding_lookup"));
    Value lookup = func_.getArgument(1);
    Value value = func_.getArgument(0);
    auto output_type = func_.getFunctionType().getResult(0);

    OpBuilder builder(func_.getBody());

  }
  builder_.create<func::ReturnOp>(func_.getLoc(), ret_operands);

  auto arg_types = body.getArgumentTypes();
  auto result_types = body.getTerminator()->getOperandTypes();
  func_.setType(FunctionType::get(func_.getContext(), arg_types, result_types));
  *f = new MlirFunction(std::move(context_), std::move(module_), func_);
  return absl::OkStatus();
}

extern "C" {

		}
	}
	return nil
}

type funcInfo struct {
	*_func
	datap *moduledata
}

func (f funcInfo) valid() bool {
	return f._func != nil
}

func (f funcInfo) _Func() *Func {
	return (*Func)(unsafe.Pointer(f._func))
}

// isInlined reports whether f should be re-interpreted as a *funcinl.
func (f *_func) isInlined() bool {
	return f.entryOff == ^uint32(0) // see comment for funcinl.ones

      llvm_unreachable("no implementation.");
      return failure();
    }
  }
  return success();
}

LogicalResult QuantizeContext::Finalize() {
  MLIRContext *context = func_.getContext();
  func_.walk([&](quantfork::QuantizeRegionOp op) {
    llvm::SmallVector<Attribute, 4> input_specs;
    auto original_input_specs = op.getInputSpecs().getValue();
    for (int i = 0, e = op.getNumOperands(); i != e; ++i) {

  // CHECK-LABEL: func @unranked_shape_arg
  func.func @unranked_shape_arg(%arg0: tensor<*xi32>) -> tensor<*xi32> {