return CartesianSet.create(sets);
  }

  /**
   * Returns every possible list that can be formed by choosing one element from each of the given
   * sets in order; the "n-ary <a href="http://en.wikipedia.org/wiki/Cartesian_product">Cartesian
   * product</a>" of the sets. For example:
   *
   * <pre>{@code
   * Sets.cartesianProduct(

    return CartesianSet.create(sets);
  }

  /**
   * Returns every possible list that can be formed by choosing one element from each of the given
   * sets in order; the "n-ary <a href="http://en.wikipedia.org/wiki/Cartesian_product">Cartesian
   * product</a>" of the sets. For example:
   *
   * <pre>{@code
   * Sets.cartesianProduct(

  NodeDef def;
  def.set_op(op_name);
  def.set_name(node_name);
  def.set_device(device_name);
  def.add_input("input1");
  def.add_input("input2");
  def.add_input("input3");
  def.add_input("input3");
  def.add_input("input3");

  AttrValue v0;
  v0.set_type(DataType::DT_INT32);
  v0.set_i(3);
  (*def.mutable_attr())["NumInput3"] = v0;
  AttrValue v1;

        https://github.com/kubernetes/kubernetes/raw/master/cluster/gce/windows/k8s-node-setup.psm1 `
        -OutFile C:\k8s-node-setup.psm1
    Invoke-WebRequest `
        https://github.com/kubernetes/kubernetes/raw/master/cluster/gce/windows/configure.ps1 `
        -OutFile C:\configure.ps1
    Import-Module -Force C:\k8s-node-setup.psm1  # -Force to override existing
    # Execute functions manually or run configure.ps1.
#>

		prologue.To = obj.Addr{Type: obj.TYPE_MEM, Reg: REG_SP, Offset: -stacksize}

		// Insert stack adjustment.
		prologue = obj.Appendp(prologue, newprog)
		prologue.As = AADDI
		prologue.From = obj.Addr{Type: obj.TYPE_CONST, Offset: -stacksize}
		prologue.Reg = REG_SP
		prologue.To = obj.Addr{Type: obj.TYPE_REG, Reg: REG_SP}
		prologue.Spadj = int32(stacksize)

          if (TF::TensorListSetItemOp set_op =
                  llvm::dyn_cast<TF::TensorListSetItemOp>(use.getOwner())) {
            element_shape = rewriter.create<TF::ShapeOp>(
                op.getLoc(),
                tensorflow::GetTypeFromTFTensorShape({-1}, shape_dtype),
                set_op.getItem());
            element_shape_acquired = true;

}

int FindReturnIndex(Value val) {
  const int not_found = -1;
  for (auto user : val.getUsers()) {
    if (auto ret_op = llvm::dyn_cast<func::ReturnOp>(user)) {
      for (auto index = 0; index < ret_op->getNumOperands(); ++index) {
        if (val == ret_op->getOperand(index)) {
          return index;
        }
      }
    }
    if (auto ident_op = llvm::dyn_cast<TF::IdentityOp>(user)) {

	IFT_SMDSICIP                  = 0x34
	IFT_SN                        = 0x38
	IFT_SONET                     = 0x27
	IFT_SONETPATH                 = 0x32
	IFT_SONETVT                   = 0x33
	IFT_SP                        = 0x39
	IFT_STARLAN                   = 0xb
	IFT_T1                        = 0x12
	IFT_TUNNEL                    = 0x3b
	IFT_ULTRA                     = 0x1d
	IFT_V35                       = 0x2d

	IFT_SMDSICIP                  = 0x34
	IFT_SN                        = 0x38
	IFT_SONET                     = 0x27
	IFT_SONETPATH                 = 0x32
	IFT_SONETVT                   = 0x33
	IFT_SP                        = 0x39
	IFT_STARLAN                   = 0xb
	IFT_T1                        = 0x12
	IFT_TUNNEL                    = 0x3b
	IFT_ULTRA                     = 0x1d
	IFT_V35                       = 0x2d

    bool reuse_existing_functions, FunctionLibraryDefinition* library) {
  // name_in is copied here because name may be modified below if
  // rewrite_subgraph_fn is true.
  string name = name_in;
  call_node_def_.set_op(name);
  call_node_def_.set_name(name);
  call_node_def_.set_device(device_);

  if (rewrite_subgraph_fn) {
    std::vector<OutputTensor> arg_source_tensors(args_by_src_.size());