Bubbles up sharding configuration from `cluster_func` regions into
    the attributes of `cluster_func`. This is done by parsing the
    `XlaSharding` / `TPUPartitionedOutput` / `TPUPartitionedInput` ops inside
    `cluster_func`.

    For example, given the following `cluster_func` wrapping `func`:

    ```mlir
      func @test(%arg0: tensor<*xi32>) {
        "tf_device.cluster_func"(%arg0) {
            func = @func,

}

void TPUAnnotateDynamicShapeInputsPass::runOnOperation() {
  getOperation().walk([&](tf_device::ClusterFuncOp cluster_func_op) {
    Builder builder(cluster_func_op->getContext());
    // Skip non-tpu device cluster_func.
    auto cluster_id =
        cluster_func_op->getAttrOfType<StringAttr>(TF::kReplicationInfoAttr);
    if (!cluster_id) return WalkResult::advance();

    llvm::SmallVector<int, 4> dynamic_shape_arg_index;

  ReplaceClusterReturnWithReturn(return_op, builder);

  symbol_table->insert(outlined_func);
  return outlined_func;
}

// Outlines body of `tf_device.cluster` into a function and create a
// `tf_device.cluster_func` to invoke that function. `tf_device.cluster` is
// removed afterwards.`
void OutlineCluster(tf_device::ClusterOp cluster_op, SymbolTable* symbol_table,
                    OpBuilder* builder) {

  let summary = "Invokes a program via IFRT on a device";

  let description = [{
    This op calls an IFRT program uniquely identified by the given program id.

    During lowering from a `tf_device.cluster_func` op to a `tf.IfrtCall` op,
    the region owned by the former will be outlined to a function with a
    `tfrt_ifrt_serving.program_id` attribute. After that, the runtime ensures

    This pass outlines the body of a `tf_device.cluster` into a function and
    replaces the `tf_device.cluster` op with an equivalent `tf_device.cluster_func`
    op. Implicit operands will be captured and materialized as explicit arguments to
    the newly created functions and associated `tf_device.cluster_func` ops.

    For example, the following:

    ```mlir
    func @computation(%arg0: tensor<i32>) -> tensor<i32> {

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_device.cc.inc"
      >();

  addInterfaces<TFInlinerInterface>();
}

//===----------------------------------------------------------------------===//
// tf_device.cluster_func
//===----------------------------------------------------------------------===//

LogicalResult ClusterFuncOp::verifySymbolUses(
    mlir::SymbolTableCollection& symbolTable) {

                            Operation* parent, MetadataMap& metadata_map) {
  std::string cluster_succ = "";
  if (op->hasAttr(TF::kTpuReplicateAttr)) {
    cluster_succ = op->getAttrOfType<StringAttr>(TF::kTpuReplicateAttr).str();
  }
  if (cluster_succ.empty()) {
    // TODO (b/269195256#comment16): Change to error after resolving issue