SP_DeviceMemoryBase* const device_dst,
                       const SP_DeviceMemoryBase* const device_src,
                       uint64_t size, TF_Status* const status) {
    TF_SetStatus(status, TF_OK, "");
    std::memcpy(device_dst->opaque, device_src->opaque, size);
  };

  StreamExecutor* executor = GetExecutor(0);

  mlir::func::registerAllExtensions(registry);
  // clang-format on
}

Status MlirFunctionOptimizationPass::Run(
    const std::string& function_name, const DeviceSet& device_set,
    const ConfigProto& config_proto,
    const FunctionOptimizationPass::FunctionOptions& function_options,
    std::unique_ptr<Graph>* graph, FunctionLibraryDefinition* flib_def,

  AttrValue index_attr;
  index_attr.set_i(index);
  (*node_def->mutable_attr())["index"] = index_attr;

  if (auto device_attr =
          func.getArgAttrOfType<mlir::StringAttr>(index, kDeviceAttr))
    *node_def->mutable_device() = device_attr.getValue().str();

  llvm::ArrayRef<mlir::NamedAttribute> func_arg_i_attrs =
      mlir::function_interface_impl::getArgAttrs(func, index);

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_saved_model.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/convert_tensor.h"
#include "tensorflow/core/common_runtime/device.h"
#include "tensorflow/core/common_runtime/device_mgr.h"
#include "tensorflow/core/framework/resource_mgr.h"
#include "tensorflow/core/framework/resource_var.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/platform/errors.h"

      absl::string_view device_name) {
    TF_ASSIGN_OR_RETURN(DeviceId device_id, GetIdFor(device_name));
    return std::cref(*id_to_device_type_[device_id.id()]);
  }

  string DebugString(const DeviceSet& device_set) const;

 private:
  absl::flat_hash_map<string, DeviceId> name_to_id_;

  // These fields are populated for a device in GetIdFor, *before* we give out a
  // DeviceId.

#include "xla/client/xla_builder.h"
#include "xla/mlir_hlo/mhlo/IR/hlo_ops.h"
#include "tensorflow/core/common_runtime/device.h"
#include "tensorflow/core/common_runtime/device_factory.h"
#include "tensorflow/core/common_runtime/device_mgr.h"
#include "tensorflow/core/common_runtime/process_function_library_runtime.h"
#include "tensorflow/core/framework/allocator.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/function.pb.h"

    params after the creation of Estimator, leading to potentially undefined
    behavior.
*   Added None check for save_path in `saver.restore`.
*   Register devices under their legacy names in device_mgr to ease the
    transition to clusterspec-propagated configurations.
*   VectorExponential added to distributions.
*   Add a bitwise module with bitwise_and, bitwise_or, bitwise_xor, and invert
    functions.