TypeID::get<TF::ComplexAbsOp>(),
        TypeID::get<TF::ConjugateTransposeOp>(),
        TypeID::get<TF::ConcatV2Op>(),
        TypeID::get<TF::ConvOp>(),
        TypeID::get<TF::CoshOp>(),
        TypeID::get<TF::CrossOp>(),
        TypeID::get<TF::CumulativeLogsumexpOp>(),
        TypeID::get<TF::DataFormatDimMapOp>(),
        TypeID::get<TF::DataFormatVecPermuteOp>(),

		name             string
		metaArr          []FileInfo
		errs             []error
		dataErrs         map[int][]int
		expectedMeta     FileInfo
		expectedDangling bool
	}{
		{
			name: "FileInfoExists-case1",
			metaArr: []FileInfo{
				{},
				{},
				fi,
				fi,
			},
			errs: []error{
				errFileNotFound,
				errDiskNotFound,
				nil,
				nil,
			},
			dataErrs:         nil,

		expectedPriorities   framework.NodeScoreList
		nodeResourcesFitArgs config.NodeResourcesFitArgs
		runPreScore          bool
	}{
		{
			name: "test case for ScoringStrategy RequestedToCapacityRatio case1",
			requestedPod: st.MakePod().
				Req(map[v1.ResourceName]string{"cpu": "3000", "memory": "5000"}).
				Obj(),
			nodes: []*v1.Node{

func clear1() {
	var a [10]int
	var m map[float64]string
	var s []byte
	clear(a /* ERROR "cannot clear a" */)
	clear(&/* ERROR "cannot clear &a" */a)
	clear(m)
	clear(s)
	clear([]int{})
}

func close1() {
	var c chan int
	var r <-chan int
	close() // ERROR "not enough arguments"
	close(1, 2) // ERROR "too many arguments"
	close(42 /* ERROR "cannot close non-channel" */)

INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(CollectiveReduceOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(ConjOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(CosOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(CoshOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(CrossOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(DataFormatDimMapOp);
INFER_RETURN_TYPE_COMPONENTS_FROM_OPERANDS(DataFormatVecPermuteOp);

*   Enable JIT-compiled i64-indexed kernels on GPU for large tensors with more than 2**32 elements.
    *   Unary GPU kernels: Abs, Atanh, Acos, Acosh, Asin, Asinh, Atan, Cos, Cosh, Sin, Sinh, Tan, Tanh.
    *   Binary GPU kernels: AddV2, Sub, Div, DivNoNan, Mul, MulNoNan, FloorDiv, Equal, NotEqual, Greater, GreaterEqual, LessEqual, Less.

* `tf.lite`

    static bool isCompatibleReturnTypes(TypeRange inferred, TypeRange actual) {
      return ArraysAreCastCompatible(inferred, actual);
    }
  }];
}

def TF_CoshOp : TF_Op<"Cosh", [Pure, TF_SameOperandsAndResultTypeResolveRef]> {
  let summary = "Computes hyperbolic cosine of x element-wise.";

  let description = [{
Given an input tensor, this function computes hyperbolic cosine of every