v_0 := v.Args[0]
	// match: (ANDI [0] x)
	// result: (MOVDconst [0])
	for {
		if auxIntToInt64(v.AuxInt) != 0 {
			break
		}
		v.reset(OpRISCV64MOVDconst)
		v.AuxInt = int64ToAuxInt(0)
		return true
	}
	// match: (ANDI [-1] x)
	// result: x
	for {
		if auxIntToInt64(v.AuxInt) != -1 {
			break
		}
		x := v_0
		v.copyOf(x)
		return true
	}

GoUnblock dt=7 g=57 g_seq=11 stack=0
GoStart dt=3 g=57 g_seq=12
GoLabel dt=2 label_string=2
GoBlock dt=1049 reason_string=15 stack=5
GoUnblock dt=23 g=58 g_seq=7 stack=0
GoStart dt=8 g=58 g_seq=8
GoLabel dt=1 label_string=2
GoBlock dt=1126 reason_string=15 stack=5
GoUnblock dt=12 g=53 g_seq=3 stack=0
GoStart dt=5 g=53 g_seq=4
GoLabel dt=1 label_string=2
GoBlock dt=1751 reason_string=15 stack=5
GoUnblock dt=12 g=53 g_seq=5 stack=0

    %cst_0 = "tf.Const"() {value = dense<2> : tensor<1xi32>} : () -> tensor<1xi32>
    %0 = "tf.StridedSlice"(%arg0, %cst_0, %cst, %cst_0) {_XlaHasReferenceVars = false, begin_mask = 0 : i64, device = "/job:localhost/replica:0/task:0/device:XLA_CPU:0", ellipsis_mask = 0 : i64, end_mask = 0 : i64, new_axis_mask = 0 : i64, shrink_axis_mask = 0 : i64} : (tensor<10xf64>, tensor<1xi32>, tensor<1xi32>, tensor<1xi32>) -> tensor<?xf64>

		{TypeOf(int(0)), ""},
		{TypeOf(int8(0)), ""},
		{TypeOf(int16(0)), ""},
		{TypeOf(int32(0)), ""},
		{TypeOf(int64(0)), ""},
		{TypeOf(uint(0)), ""},
		{TypeOf(uint8(0)), ""},
		{TypeOf(uint16(0)), ""},
		{TypeOf(uint32(0)), ""},
		{TypeOf(uint64(0)), ""},
		{TypeOf(uintptr(0)), ""},
		{TypeOf(float32(0)), ""},
		{TypeOf(float64(0)), ""},
		{TypeOf(complex64(0)), ""},

				startTime: func() *time.Time {
					now := time.Now()
					return &now
				}(),
			},
			activePods:         0,
			succeededPods:      0,
			expectedCreations:  0,
			expectedActive:     0,
			expectedSucceeded:  0,
			expectedPodPatches: 0,
			expectedReady:      ptr.To[int32](0),
			controllerTime:     &referenceTime,
		},
		"too few active pods and no back-offs": {
			parallelism:  1,

        // expected-remark@above {{ID: 0}}
        "tf.MakeIterator"(%arg0, %handle) {_class = ["loc:@GeneratorDataset_2"], device = "/job:tpu_host_worker/replica:0/task:0/device:CPU:0"} : (tensor<!tf_type.variant>, tensor<!tf_type.resource>) -> ()

  return success();
}

OpFoldResult StridedSliceOp::fold(FoldAdaptor) {
  // Currently only support all masks being 0.
  if (getBeginMask() != 0 || getEndMask() != 0 || getEllipsisMask() != 0 ||
      getNewAxisMask() != 0 || getShrinkAxisMask() != 0)
    return {};

  auto input_type = getInput().getType().dyn_cast_or_null<RankedTensorType>();

	{as: obj.APCDATA, a1: C_32CON, a6: C_32CON, type_: 0, size: 0},
	{as: obj.AFUNCDATA, a1: C_U15CON, a6: C_ADDR, type_: 0, size: 0},
	{as: obj.ANOP, type_: 0, size: 0},
	{as: obj.ANOP, a1: C_32CON, type_: 0, size: 0}, // NOP operand variations added for #40689
	{as: obj.ANOP, a1: C_REG, type_: 0, size: 0},   // to preserve previous behavior
	{as: obj.ANOP, a1: C_FREG, type_: 0, size: 0},

}

var ytext = []ytab{
	{Zpseudo, 0, argList{Ymb, Ytextsize}},
	{Zpseudo, 1, argList{Ymb, Yi32, Ytextsize}},
}

var ynop = []ytab{
	{Zpseudo, 0, argList{}},
	{Zpseudo, 0, argList{Yiauto}},
	{Zpseudo, 0, argList{Yml}},
	{Zpseudo, 0, argList{Yrf}},
	{Zpseudo, 0, argList{Yxr}},
	{Zpseudo, 0, argList{Yiauto}},
	{Zpseudo, 0, argList{Yml}},
	{Zpseudo, 0, argList{Yrf}},
	{Zpseudo, 1, argList{Yxr}},
}

	ldr.SetSymSect(ldr.LookupOrCreateSym("runtime.cutab", 0), sect)
	ldr.SetSymSect(ldr.LookupOrCreateSym("runtime.filetab", 0), sect)
	ldr.SetSymSect(ldr.LookupOrCreateSym("runtime.pctab", 0), sect)
	ldr.SetSymSect(ldr.LookupOrCreateSym("runtime.functab", 0), sect)
	ldr.SetSymSect(ldr.LookupOrCreateSym("runtime.epclntab", 0), sect)
	setCarrierSize(sym.SPCLNTAB, int64(sect.Length))
	if ctxt.HeadType == objabi.Haix {