Value CreateZeroInput(Location loc, OpBuilder& builder, Attribute zero_attr,
                      DenseIntElementsAttr shape_attr) {
  ConstOp zero = builder.create<ConstOp>(loc, zero_attr);
  zero->setAttr(kICIWeightDistributionMlirBridgeMarker,
                builder.getBoolAttr(true));
  ConstOp shape = builder.create<ConstOp>(loc, shape_attr);
  shape->setAttr(kICIWeightDistributionMlirBridgeMarker,
                 builder.getBoolAttr(true));

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

namespace tflite {
namespace {

bool IsConst(mlir::Operation* op) {
  return llvm::isa<mlir::arith::ConstantOp, mlir::TF::ConstOp,
                   mlir::TFL::ConstOp, mlir::TFL::QConstOp>(op);
}

bool IsOpSupported(mlir::Operation* op, const std::string& hardware) {
  auto* devce_hardware = mlir::TFL::tac::GetTargetHardware(hardware);

	tests := []struct {
		name       string
		pod        *v1.Pod
		node       *v1.Node
		wantStatus *framework.Status
	}{
		{
			name: "A pod having no tolerations can't be scheduled onto a node with nonempty taints",
			pod:  podWithTolerations("pod1", []v1.Toleration{}),
			node: nodeWithTaints("nodeA", []v1.Taint{{Key: "dedicated", Value: "user1", Effect: "NoSchedule"}}),

		wantErr            bool
	}{
		{
			name:             "returns expected secret summary onto Stdout",
			callPrime:        true,
			wantOutputSecret: "testdata/secretsummary.txt",
		},
		{
			name:    "errors if config dump is not primed",
			wantErr: true,
		},
		{
			name:               "returns expected workload summary onto Stdout",
			callPrime:          true,
			wantOutputWorkload: "testdata/workloadsummary.txt",
		},

// converted to an ElementsAttr and then those are packed together using
// tf.Pack op.
struct ConvertConst : public OpConversionPattern<TF::ConstOp> {
  using OpConversionPattern::OpConversionPattern;

  LogicalResult matchAndRewrite(
      TF::ConstOp op, OpAdaptor adaptor,
      ConversionPatternRewriter &rewriter) const override {
    // Verify that the tensor proto contains tensor of type variant and scalar

    //    executing listeners in the order they were added
    // 3. push all the items onto 'onto' and return the new head of the stack
    Listener head = ATOMIC_HELPER.gasListeners(this, Listener.TOMBSTONE);
    Listener reversedList = onto;
    while (head != null) {
      Listener tmp = head;
      head = head.next;
      tmp.next = reversedList;
      reversedList = tmp;

    //    executing listeners in the order they were added
    // 3. push all the items onto 'onto' and return the new head of the stack
    Listener head = ATOMIC_HELPER.gasListeners(this, Listener.TOMBSTONE);
    Listener reversedList = onto;
    while (head != null) {
      Listener tmp = head;
      head = head.next;
      tmp.next = reversedList;
      reversedList = tmp;

  return Status(absl::StatusCode::kInvalidArgument, "Unsupported type");
}

static bool IsConst(Operation* op) {
  return isa<mlir::func::ConstantOp, mlir::arith::ConstantOp, mlir::TF::ConstOp,
             tfl::ConstOp, tfl::QConstOp, tfl::SparseConstOp,
             tfl::SparseQConstOp, mlir::TFL::NoValueOp,
             mlir::stablehlo::ConstantOp, mlir::vhlo::ConstantOpV1>(op);
}

  OpBuilder builder(&func.front().front());
  for (auto arg : func.getArguments()) {
    Value operand = op.getOperand(arg.getArgNumber());
    if (isa_and_nonnull<TF::ConstOp>(operand.getDefiningOp())) {
      xla_recv_at_host_op.getResult(arg.getArgNumber())
          .replaceAllUsesWith(
              builder.clone(*operand.getDefiningOp())->getResult(0));
    }
  }

	}
	return configgen.buildClusters(proxy, req, services)
}

// BuildDeltaClusters generates the deltas (add and delete) for a given proxy. Currently, only service changes are reflected with deltas.
// Otherwise, we fall back onto generating everything.
func (configgen *ConfigGeneratorImpl) BuildDeltaClusters(proxy *model.Proxy, updates *model.PushRequest,
	watched *model.WatchedResource,
) ([]*discovery.Resource, []string, model.XdsLogDetails, bool) {