mlir::func::FuncOp func, Builder* builder,
    OptionalOpShardingVector& sharding_for_args) {
  // Look up function definition from module.
  Block& function_block = func.front();

  sharding_for_args.reserve(function_block.getNumArguments());

  // Iterate through operands of `cluster_func`.
  // The computation operand can either be:
  //   1) a TPUPartitionedInput Op if the input has a non-resource type;

	// if called from a non-go thread.
	XORPS	X15, X15
	XORQ	R14, R14

	get_tls(AX)
	CMPQ	AX, $0
	JE	2(PC)
	// Exception from Go thread, set R14.
	MOVQ	g(AX), R14

	// Reserve space for spill slots.
	ADJSP	$16
	MOVQ	CX, AX
	MOVQ	DX, BX
	// Calling ABIInternal because TLS might be nil.
	CALL	runtime·sigtrampgo<ABIInternal>(SB)
	// Return value is already stored in AX.

    tensorflow::shape_inference::InferenceContext* ic, int num_dims,
    const int64_t* dims) {
  if (num_dims != -1) {
    std::vector<tensorflow::shape_inference::DimensionHandle> dim_vec;
    dim_vec.reserve(num_dims);
    for (int i = 0; i < num_dims; ++i) {
      dim_vec.push_back(ic->MakeDim(dims[i]));
    }
    return ic->MakeShape(dim_vec);
  } else {
    return ic->UnknownShape();
  }
}

ConvertI64ArrayAttrForOptionWriter(mlir::ArrayAttr attrArray,
                                   flatbuffers::FlatBufferBuilder* builder) {
  std::vector<int32_t> intVec;
  intVec.reserve(attrArray.getValue().size());
  for (auto attr : attrArray.getValue()) {
    intVec.push_back(mlir::cast<mlir::IntegerAttr>(attr).getInt());
  }
  return builder->CreateVector(intVec);
}

	// update qos cgroup tiers on startup and in periodic intervals
	// to ensure desired state is in sync with actual state.
	go wait.Until(func() {
		err := m.UpdateCgroups()
		if err != nil {
			klog.InfoS("Failed to reserve QoS requests", "err", err)
		}
	}, periodicQOSCgroupUpdateInterval, wait.NeverStop)

	return nil
}

// setHugePagesUnbounded ensures hugetlb is effectively unbounded

		// remaining time.
		if gp := timeout / 20; gp > gracePeriod {
			gracePeriod = gp
		}

		// When we run commands that execute subprocesses, we want to reserve two
		// grace periods to clean up. We will send the first termination signal when
		// the context expires, then wait one grace period for the process to
		// produce whatever useful output it can (such as a stack trace). After the

  std::vector<int64_t> size_as_vector;
};

std::vector<int64_t> IntTensorAsVector(const Tensor& t) {
  DCHECK(t.dtype() == DT_INT32 || t.dtype() == DT_INT64);
  std::vector<int64_t> result;
  result.reserve(t.NumElements());
  for (int i = 0; i < t.NumElements(); i++) {
    int64_t element = t.dtype() == DT_INT32
                          ? static_cast<int64_t>(t.flat<int32>()(i))
                          : t.flat<int64_t>()(i);

}

Value GetR1Const(ArrayRef<int64_t> r1, OpBuilder builder, Location loc,
                 int bitwidth) {
  llvm::SmallVector<APInt, 4> values;
  int64_t rank = r1.size();
  values.reserve(rank);
  for (int i = 0; i < rank; ++i) values.push_back(APInt(bitwidth, r1[i]));
  auto result_type = tensorflow::GetTypeFromTFTensorShape(
      {rank}, IntegerType::get(builder.getContext(), bitwidth));

	fs.StringVar(&c.KubeReservedCgroup, "kube-reserved-cgroup", c.KubeReservedCgroup, "Absolute name of the top level cgroup that is used to manage kubernetes components for which compute resources were reserved via '--kube-reserved' flag. Ex. '/kube-reserved'. [default='']")
	logsapi.AddFlags(&c.Logging, fs)

}

// userArenaChunkReserveBytes returns the amount of additional bytes to reserve for
// heap metadata.
func userArenaChunkReserveBytes() uintptr {
	// In the allocation headers experiment, we reserve the end of the chunk for
	// a pointer/scalar bitmap. We also reserve space for a dummy _type that
	// refers to the bitmap. The PtrBytes field of the dummy _type indicates how