&devices);
  if (!status->status.ok()) return nullptr;
  std::unique_ptr<tensorflow::DeviceMgr> device_mgr(
      new tensorflow::DynamicDeviceMgr(std::move(devices)));

  auto r = tsl::core::RefCountPtr<tensorflow::IntraProcessRendezvous>(
      new tensorflow::IntraProcessRendezvous(device_mgr.get()));
  tensorflow::EagerContext* eager_context = new tensorflow::EagerContext(
      opts->session_options.options,

#include "tensorflow/compiler/tf2xla/functionalize_control_flow.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/grappler/clusters/virtual_cluster.h"
#include "tensorflow/core/grappler/grappler_item.h"
#include "tensorflow/core/grappler/grappler_item_builder.h"

#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"

    return CreateSessionInitFunc(module);
  }
}

}  // namespace

LogicalResult InitializeVariablesInSessionInitializer(
    ModuleOp module, tensorflow::Session* session) {
  const tensorflow::DeviceMgr* mgr = nullptr;
  auto status = session->LocalDeviceManager(&mgr);
  if (!status.ok()) {
    module->emitError(
        absl::StrCat("failed to fetch device manager: ", status.message()));
    return failure();
  }

#include "tensorflow/core/platform/mutex.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/public/session.h"

namespace tensorflow {
class Device;
class DeviceMgr;
class ServerInterface;
}  // namespace tensorflow

// Internal structures used by the C API. These are likely to change and should
// not be depended on.

struct TF_SessionOptions {

}

// Returns ElementsAttr which has the value held by 'resource_tensor'.
ElementsAttr GetTensorValueAsElementsAttr(
    TF::VarHandleOp var_handle_op, const tensorflow::Tensor& resource_tensor,
    const tensorflow::DeviceMgr* mgr, OpBuilder builder) {
  if (resource_tensor.dtype() != tensorflow::DT_RESOURCE) {
    return GetTensorValueAsElementsAttr(resource_tensor, builder);
  }

  }

  std::unique_ptr<DeviceMgr> device_mgr =
      std::make_unique<StaticDeviceMgr>(std::move(devices));
  const auto* config = &options.session_options->config;
  std::unique_ptr<ProcessFunctionLibraryRuntime> pflr(
      new ProcessFunctionLibraryRuntime(
          device_mgr.get(), options.session_options->env,
          /*config=*/config, TF_GRAPH_DEF_VERSION, library,

  TF_CHECK_OK(DeviceFactory::AddDevices(
      session_options, "/job:localhost/replica:0/task:0", &devices));
  OptimizerOptions opts;
  auto device_mgr = std::make_unique<StaticDeviceMgr>(std::move(devices));
  auto pflr = std::make_unique<ProcessFunctionLibraryRuntime>(
      device_mgr.get(), Env::Default(), /*config=*/nullptr,
      TF_GRAPH_DEF_VERSION, lib_def.get(), opts,
      /*default_thread_pool=*/nullptr, /*cluster_flr=*/nullptr);

#include "tensorflow/c/c_api_internal.h"
#include "tensorflow/c/tf_buffer_internal.h"
#include "tensorflow/c/tf_status_internal.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/common_runtime/device_mgr.h"
#include "tensorflow/core/common_runtime/eval_const_tensor.h"
#include "tensorflow/core/common_runtime/graph_constructor.h"
#include "tensorflow/core/common_runtime/shape_refiner.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.