return iAddr < jAddr
		}
		iType := retrieveListenerType(verifiedListeners[i])
		jType := retrieveListenerType(verifiedListeners[j])
		return iType < jType
	})

	printStr := "ADDRESSES\tPORT"
	if includeConfigType {
		printStr = "NAME\t" + printStr
	}
	if filter.Verbose {
		printStr += "\tMATCH\tDESTINATION"
	} else {
		printStr += "\tTYPE"
	}
	fmt.Fprintln(w, printStr)

        type, builder.getFloatAttr(element_ty, unique_index));

  if (auto qtype = mlir::dyn_cast<QuantizedType>(element_ty)) {
    mlir::RankedTensorType new_type = tensorflow::GetTypeFromTFTensorShape(
        type.getShape(), qtype.getStorageType());
    return DenseElementsAttr::get(
        new_type, builder.getIntegerAttr(qtype.getStorageType(), unique_index));
  }
  llvm_unreachable("unhandled element type");
}

	stringEface any = stringInterfacePtr("")
	sliceEface  any = sliceInterfacePtr(nil)

	uint16Type *_type = efaceOf(&uint16Eface)._type
	uint32Type *_type = efaceOf(&uint32Eface)._type
	uint64Type *_type = efaceOf(&uint64Eface)._type
	stringType *_type = efaceOf(&stringEface)._type
	sliceType  *_type = efaceOf(&sliceEface)._type
)

// The conv and assert functions below do very similar things.

			except Exception as e:
				print("Can't parse ", obj, ": ", e)
				continue

			if obj['data'] == 0:
				dtype = "nil"
			else:
				dtype = iface_dtype(obj)

			if dtype is None:
				print("Not an interface: ", obj.type)
				continue

			print("{0}: {1}".format(obj.type, dtype))

# TODO: print interface's methods and dynamic type's func pointers thereof.

// license that can be found in the LICENSE file.

// Runtime type representation.

package runtime

import (
	"internal/abi"
	"unsafe"
)

type nameOff = abi.NameOff
type typeOff = abi.TypeOff
type textOff = abi.TextOff

type _type = abi.Type

// rtype is a wrapper that allows us to define additional methods.
type rtype struct {
	*abi.Type // embedding is okay here (unlike reflect) because none of this is public

	return s[i+1:]
}

func toRType(t *abi.Type) rtype {
	return rtype{t}
}

func elem(t *abi.Type) *abi.Type {
	et := t.Elem()
	if et != nil {
		return et
	}
	panic("reflect: Elem of invalid type " + toRType(t).String())
}

func (t rtype) Elem() Type {
	return toType(elem(t.common()))
}

func (t rtype) In(i int) Type {
	tt := t.Type.FuncType()
	if tt == nil {

type UcharType struct {
	BasicType
}

// An IntType represents a signed integer type.
type IntType struct {
	BasicType
}

// A UintType represents an unsigned integer type.
type UintType struct {
	BasicType
}

// A FloatType represents a floating point type.
type FloatType struct {
	BasicType
}

// A ComplexType represents a complex floating point type.
type ComplexType struct {

}

// Imethod represents a method on an interface type
type Imethod struct {
	Name NameOff // name of method
	Typ  TypeOff // .(*FuncType) underneath
}

// ArrayType represents a fixed array type.
type ArrayType struct {
	Type
	Elem  *Type // array element type
	Slice *Type // slice type
	Len   uintptr
}

// Len returns the length of t if t is an array type, otherwise 0
func (t *Type) Len() int {

)

// userTypeInfo stores the information associated with a type the user has handed
// to the package. It's computed once and stored in a map keyed by reflection
// type.
type userTypeInfo struct {
	user        reflect.Type // the type the user handed us
	base        reflect.Type // the base type after all indirections
	indir       int          // number of indirections to reach the base type
	externalEnc int          // xGob, xBinary, or xText

    return mlir::TF::ShapeAttr::get(type.getContext(), tensor_type.getShape());
  }

  // If type is not a RankedTensor or UnrankedTensor, it must be a scalar.
  // Empty TensorShape indicates a scalar.
  return mlir::TF::ShapeAttr::get(type.getContext(), ArrayRef<int64_t>());
}

absl::StatusOr<TensorSpecProto> ConvertTypeToTensorSpecProto(
    const mlir::Type& type) {
  DataType dtype;