friend TestInfo* internal::MakeAndRegisterTestInfo(
      const char* test_case_name,
      const char* name,
      const char* type_param,
      const char* value_param,
      internal::TypeId fixture_class_id,
      Test::SetUpTestCaseFunc set_up_tc,
      Test::TearDownTestCaseFunc tear_down_tc,
      internal::TestFactoryBase* factory);

// TFR Dialect
//===----------------------------------------------------------------------===//

TFRDialect::TFRDialect(MLIRContext *context)
    : Dialect(/*name=*/"tfr", context, TypeID::get<TFRDialect>()) {
  // TFR depends on TensorFlow for its canonicalization
  context->getOrLoadDialect<TF::TensorFlowDialect>();

  addTypes<TFRTensorType, TFRTensorListType, TFRAttrType>();
  addOperations<

		if err == io.EOF {
			break
		}
		if err != nil {
			return fmt.Errorf("next: %v", err)
		}

		dest := filepath.Join(destination, header.Name)
		switch header.Typeflag {
		case tar.TypeDir:
			if _, err := os.Stat(dest); err != nil {
				if err := os.Mkdir(dest, 0o755); err != nil {
					return fmt.Errorf("mkdir: %v", err)
				}
			}
		case tar.TypeReg:

// of the max int boundary.
// We do it this way so the test doesn't depend on ints being 32 bits.
var (
	bigInt  = fmt.Sprintf("0x%x", int(1<<uint(reflect.TypeFor[int]().Bits()-1)-1))
	bigUint = fmt.Sprintf("0x%x", uint(1<<uint(reflect.TypeFor[int]().Bits()-1)))
)

var execTests = []execTest{
	// Trivial cases.
	{"empty", "", "", nil, true},
	{"text", "some text", "some text", nil, true},

	defaultSampleTypeX int64
}

// ValueType corresponds to Profile.ValueType
type ValueType struct {
	Type string // cpu, wall, inuse_space, etc
	Unit string // seconds, nanoseconds, bytes, etc

	typeX int64
	unitX int64
}

// Sample corresponds to Profile.Sample
type Sample struct {
	Location []*Location
	Value    []int64
	// Label is a per-label-key map to values for string labels.
	//

	o.X = typ
	return o
}

// typeOrNil is like type_ but it returns nil if there was no type
// instead of reporting an error.
//
//	Type     = TypeName | TypeLit | "(" Type ")" .
//	TypeName = identifier | QualifiedIdent .
//	TypeLit  = ArrayType | StructType | PointerType | FunctionType | InterfaceType |
//		      SliceType | MapType | Channel_Type .
func (p *parser) typeOrNil() Expr {
	if trace {

  }
};

}  // namespace

TensorFlowExecutorDialect::TensorFlowExecutorDialect(MLIRContext *context)
    : Dialect(/*name=*/"tf_executor", context,
              TypeID::get<TensorFlowExecutorDialect>()) {
  addOperations<
#define GET_OP_LIST
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_executor.cc.inc"
      >();

  addInterfaces<TensorFlowExecutorInlinerInterface,

				"GNU.sparse.realsize": "1000",
				"GNU.sparse.name":     "sparse.db",
			},
			Format: FormatPAX,
		}},
	}, {
		file: "testdata/trailing-slash.tar",
		headers: []*Header{{
			Typeflag: TypeDir,
			Name:     strings.Repeat("123456789/", 30),
			ModTime:  time.Unix(0, 0),
			PAXRecords: map[string]string{
				"path": strings.Repeat("123456789/", 30),
			},
			Format: FormatPAX,
		}},
	}}

		tt := (*structType)(unsafe.Pointer(t))
		for i := range tt.Fields {
			f := &tt.Fields[i]
			addTypeBits(bv, offset+f.Offset, f.Typ)
		}
	}
}

// TypeFor returns the [Type] that represents the type argument T.
func TypeFor[T any]() Type {
	var v T
	if t := TypeOf(v); t != nil {
		return t // optimize for T being a non-interface kind
	}
	return TypeOf((*T)(nil)).Elem() // only for an interface kind

	"sZ": {"sizeof...", 1, precUnary},
	"sc": {"static_cast", 2, precPostfix},
	"ss": {"<=>", 2, precSpaceship},
	"st": {"sizeof ", 1, precUnary},
	"sz": {"sizeof ", 1, precUnary},
	"te": {"typeid ", 1, precPostfix},
	"ti": {"typeid ", 1, precPostfix},
	"tr": {"throw", 0, precPrimary},
	"tw": {"throw ", 1, precUnary},
}

// operatorName parses:
//
//	operator_name ::= many different two character encodings.