flagVariants := make(map[string]bool)

	for _, lib := range ctxt.Library {

		consts := d.ldr.Lookup(dwarf.ConstInfoPrefix+lib.Pkg, 0)
		for _, unit := range lib.Units {
			// We drop the constants into the first CU.
			if consts != 0 {
				unit.Consts = sym.LoaderSym(consts)
				d.importInfoSymbol(consts)
				consts = 0
			}
			ctxt.compUnits = append(ctxt.compUnits, unit)

	}

	// Number of write buffer entries we can request at once.
	// Must match runtime/mwbbuf.go:wbMaxEntriesPerCall.
	// It must also match the number of instances of runtime.gcWriteBarrier{X}.
	const maxEntries = 8

	var sb, sp, wbaddr, const0 *Value
	var cgoCheckPtrWrite, cgoCheckMemmove *obj.LSym
	var wbZero, wbMove *obj.LSym
	var stores, after []*Value
	var sset, sset2 *sparseSet
	var storeNumber []int32

echo '// Code generated by the command above; DO NOT EDIT.'
echo
go tool cgo -godefs -- "$@" _const.go >_error.out
cat _error.out | grep -vf _error.grep | grep -vf _signal.grep
echo
echo '// Errors'
echo 'const ('
cat _error.out | grep -f _error.grep | sed 's/=\(.*\)/= Errno(\1)/'
echo ')'

echo
echo '// Signals'
echo 'const ('
cat _error.out | grep -f _signal.grep | sed 's/=\(.*\)/= Signal(\1)/'
echo ')'

// CHECK-DAG: %[[CONST_8:.*]] = "tf.Const"() <{value = dense<[162, 160]> : tensor<2xi32>}> : () -> tensor<2xi32>
// CHECK: %[[PADV2_0:.*]] = "tf.PadV2"({{.*}}, %[[CONST_4]], %[[CONST_5]]) : (tensor<1x3x4x3xi8>, tensor<4x2xi32>, tensor<i8>) -> tensor<1x4x5x3xi8>
// CHECK: %[[XLACONVV2_0:.*]] = "tf.XlaConvV2"(%[[PADV2_0]], %[[CONST_6]], %[[CONST_0]], %[[CONST_3]], %[[CONST_1]], %[[CONST_1]], %[[CONST_2]])

// CHECK-NEXT:     }, {
// CHECK-NEXT:       shape: [ 1, 4 ],
// CHECK-NEXT:       name: "Const",
// CHECK-NEXT:       quantization: {
// CHECK-EMPTY:
// CHECK-NEXT:       },
// CHECK-NEXT:       is_variable: true,
// CHECK-NEXT:       has_rank: true
// CHECK-NEXT:     }, {
// CHECK-NEXT:       shape: [ 1, 4 ],
// CHECK-NEXT:       name: "Const1",
// CHECK-NEXT:       quantization: {
// CHECK-EMPTY:
// CHECK-NEXT:       },

// CHECK-NEXT:     }, {
// CHECK-NEXT:       shape: [ 1, 4 ],
// CHECK-NEXT:       name: "Const",
// CHECK-NEXT:       quantization: {
// CHECK-EMPTY:
// CHECK-NEXT:       },
// CHECK-NEXT:       is_variable: true,
// CHECK-NEXT:       has_rank: true
// CHECK-NEXT:     }, {
// CHECK-NEXT:       shape: [ 1, 4 ],
// CHECK-NEXT:       name: "Const1",
// CHECK-NEXT:       quantization: {
// CHECK-EMPTY:
// CHECK-NEXT:       },

class QuantizeConstWeights : public OpRewritePattern<TF::ConstOp> {
 public:
  explicit QuantizeConstWeights(
      MLIRContext* context,
      const tensorflow::quantization::QuantizationOptions& quantization_options)
      : OpRewritePattern<TF::ConstOp>(context),
        quant_options_(quantization_options) {}

  LogicalResult matchAndRewrite(TF::ConstOp op,

DATA consts<>+0x48(SB)/8, $0x0102030005060704
DATA consts<>+0x50(SB)/8, $0x6170786561707865
DATA consts<>+0x58(SB)/8, $0x6170786561707865
DATA consts<>+0x60(SB)/8, $0x3320646e3320646e
DATA consts<>+0x68(SB)/8, $0x3320646e3320646e
DATA consts<>+0x70(SB)/8, $0x79622d3279622d32
DATA consts<>+0x78(SB)/8, $0x79622d3279622d32
DATA consts<>+0x80(SB)/8, $0x6b2065746b206574
DATA consts<>+0x88(SB)/8, $0x6b2065746b206574

// CHECK-DAG: %[[CONST_2:.+]] = stablehlo.constant dense<3> : tensor<1xi32>
// CHECK-DAG: %[[CONST_3:.+]] = stablehlo.constant dense<4> : tensor<1xi32>
// CHECK-DAG: %[[CONST_4:.+]] = stablehlo.constant dense<2> : tensor<1xi32>

    %0 = tf_executor.graph {
      %outputs, %control = tf_executor.island wraps "tf.Const"() {device = "/device:CPU:0", value = dense<[3, 32, 32, 3]> : tensor<4xi32>} : () -> tensor<4xi32>