continue
			}
			return n.Pos()
		// types
		// case *ArrayType:
		// case *SliceType:
		// case *DotsType:
		// case *StructType:
		// case *Field:
		// case *InterfaceType:
		// case *FuncType:
		// case *MapType:
		// case *ChanType:

		// statements
		// case *EmptyStmt:
		// case *LabeledStmt:
		// case *BlockStmt:
		// case *ExprStmt:
		case *SendStmt:
			m = n.Chan
		// case *DeclStmt:

	"go/parser"
	"go/token"
	"io/fs"
	"os"
	"path/filepath"
	"runtime"
	"strings"
	"sync"
	"testing"
)

var typeNames = []string{
	"uncommonType",
	"arrayType",
	"chanType",
	"funcType",
	"interfaceType",
	"ptrType",
	"sliceType",
	"structType",
}

type visitor struct {
	m map[string]map[string]bool
}

func newVisitor() visitor {
	v := visitor{}

	//     12  .  .  .  .  .  Kind: func
	//     13  .  .  .  .  .  Name: "main"
	//     14  .  .  .  .  .  Decl: *(obj @ 7)
	//     15  .  .  .  .  }
	//     16  .  .  .  }
	//     17  .  .  .  Type: *ast.FuncType {
	//     18  .  .  .  .  Func: 3:1
	//     19  .  .  .  .  Params: *ast.FieldList {
	//     20  .  .  .  .  .  Opening: 3:10
	//     21  .  .  .  .  .  Closing: 3:11
	//     22  .  .  .  .  }
	//     23  .  .  .  }

		Walk(v, n.Key)
		Walk(v, n.Value)

	// Types
	case *ArrayType:
		if n.Len != nil {
			Walk(v, n.Len)
		}
		Walk(v, n.Elt)

	case *StructType:
		Walk(v, n.Fields)

	case *FuncType:
		if n.TypeParams != nil {
			Walk(v, n.TypeParams)
		}
		if n.Params != nil {
			Walk(v, n.Params)
		}
		if n.Results != nil {
			Walk(v, n.Results)
		}

	case *InterfaceType:

    return;
  }

  OpBuilder builder(func);
  FunctionType func_type = func.getFunctionType();
  llvm::SmallVector<Type, 4> new_input_types(func_type.getInputs().begin(),
                                             func_type.getInputs().end());
  llvm::SmallVector<Type, 4> new_output_types(func_type.getResults().begin(),
                                              func_type.getResults().end());

  if (!main_fn) {
    return absl::InternalError("Could not find main function in MLIR Module.");
  }

  mlir::FunctionType func_type = main_fn.getFunctionType();
  for (auto input_type : func_type.getInputs()) {
    tensorflow::TensorShape tensor_shape;
    xla::Shape xla_shape = xla::TypeToShape(input_type);
    TF_RETURN_IF_ERROR(tensorflow::TensorShape::BuildTensorShape(

    // functions.
    auto func_names = mlir::tf_saved_model::GetExportedNames(func);
    if (func_names.empty()) return mlir::WalkResult::advance();

    auto func_type = func.getFunctionType();

    // Here we walk through each arguments and find out the input/output names,
    // and input devices, variables used by this function.
    llvm::SmallVector<llvm::StringRef, 4> input_names;

  auto return_types = llvm::to_vector<4>(terminator->getOperandTypes());

  FunctionType func_type = func.getFunctionType();
  if (llvm::ArrayRef(return_types) == func_type.getResults()) return;

  auto updated_type =
      FunctionType::get(func.getContext(), func_type.getInputs(), return_types);
  func.setType(updated_type);
}

// TODO(jpienaar): Remove when recursive side-effect modeling is added.

  llvm::SmallVector<Type, 4> operand_types;
  operand_types.reserve(live_ins.size());
  for (Value v : live_ins) operand_types.emplace_back(v.getType());

  auto func_type = builder->getFunctionType(operand_types, op.getResultTypes());

  std::string func_name;
  if (auto outlined_func_name = op->template getAttrOfType<StringAttr>(
          TF::kClusterOutlinedFunctionNameAttr)) {

    // Function results are the yield operands
    SmallVector<Type, 16> func_result_types;
    for (Value operand : island_op.GetYield().getOperands())
      func_result_types.push_back(operand.getType());
    FunctionType func_type =
        FunctionType::get(ctx, func_operand_types, func_result_types);

    // Create the outlined function
    SmallString<32> name = kOutlinedFuncPrefix;
    name += llvm::Twine(prefix_id++).str();