// For all other inputs that go from TPU op to TPU op, insert the
  // TPUOutput/Input pair.

  // Add TPUReplicatedInput/TPUReplicatedOutput pairs along each edge.
  // TODO(bfontain): Should be merged with the above loop.
  llvm::SetVector<Value> values_to_add_nodes;

  for (Operation* op : backward_pass_ops) {
    // TODO(bfontain): Should validate that all the TPU ops are in the same
    // replication region.

  getOperation().walk([&](tf_device::ClusterFuncOp cluster_func) {
    cluster_funcs.push_back(cluster_func);
  });

  OpBuilder builder(&getContext());
  // Add resource reads for resource writes from TPU cluster where for such
  // resources the TPU cluster does not read from.
  for (tf_device::ClusterFuncOp cluster_func : cluster_funcs) {
    builder.setInsertionPoint(cluster_func);

    SmallVector<Value, 4> read_operands;

#include <variant>
#include <vector>

#include "absl/strings/string_view.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"

namespace tensorflow {
namespace tf2xla {
namespace internal {

// Fills in arg_shapes and metadata_proto with appropriate values based on the
// input mlir module.

                                        const StringAttr &op_device) {
    // In TFRT TPU, tensor transfer is handled specifically by D2H and
    // H2D transfer kernels. So fold the tf.Identity op if:
    // * the identity op is placed on TPU, and
    // * the arg to the identity op is produced by a TPUExecuteOp.
    if (op_device && op_device.getValue().contains("TPU")) {
      return true;
    }

    Operation *def_op = arg.getDefiningOp();

        "//tensorflow/core:lib",
        "//tensorflow/core/platform:statusor",
        "//tensorflow/core/tpu:tpu_compile",
        "//tensorflow/core/tpu/kernels:tpu_compile_op_support",
        "//tensorflow/core/tpu/kernels:tpu_compile_proto_cc",
        "//tensorflow/core/tpu/kernels:tpu_util_hdrs",
        "@com_google_absl//absl/log",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/strings",

#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/fingerprint.h"
#include "tensorflow/core/platform/protobuf.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"
#include "tensorflow/core/util/device_name_utils.h"

namespace mlir {
namespace TFTPU {

constexpr char kStepMarkerLocationAttr[] = "step_marker_location";

#include "xla/xla.pb.h"
#include "xla/xla_data.pb.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/protobuf/tpu/compile_metadata.pb.h"

namespace mlir {
namespace TFTPU {

// Populates a TPUCompileMetadataProto from attributes of a
// `tf_device::ClusterFuncOp`. If any necessary attributes are missing from the

  }
}

// Checks if an operation can have TPU devices propagated through.
bool IsSupportedOpToSetDevice(Operation& op) {
  return IsSupportedExecutorOp(op) ||
         isa<TF::IdentityOp, TF::IdentityNOp, TF::ShapeOp>(op);
}

// Finds nonconflicting TPU device for an operation from its operands. If an
// operand has no device or a non TPU device, or if there are conflicting

CreateTFExecutorIslandCoarseningPass();

// Creates a pass to merge IslandOps for operation marked for execution on TPU.
// This is a V1 backward compatibility.
std::unique_ptr<OperationPass<ModuleOp>>
CreateTFExecutorTPUV1IslandCoarseningPass();

// Creates a pass to outlining TPU clusters from single IslandOp into a nested
// module suitable for being processed as-if it was a V2 module.

    compatible_with = get_compatible_with_portable(),  # copybara: comment
    visibility = [
        # copybara:uncomment "//learning/brain/experimental/tfrt:__subpackages__",
        # copybara:uncomment "//learning/brain/tfrt/tpu/compiler:__subpackages__",
        "//tensorflow/compiler/mlir/tfrt:__subpackages__",
        "//tensorflow/core/runtime_fallback:internal",
        "//tensorflow/core/tfrt/saved_model:friends",