// in current TF runtime. For tfrt, it is used by fallback op handler.
  virtual void StartStep() = 0;
  // Destroy the step resource container for a training step.
  virtual void EndStep() = 0;

  // Return the Eager Executor for current thread. Please note that Eager
  // Executor is only used in current TF but not in TFRT.
  virtual EagerExecutor& Executor() = 0;

      tensorflow::unwrap(ctx)->GetDistributedManager();
  tsl::CoordinationServiceAgent* coord_agent =
      dist_mgr->GetCoordinationServiceAgent();
  if (coord_agent == nullptr) {
    status->status = tensorflow::errors::FailedPrecondition(
        "Coordination service agent is not enabled.");
    return;
  }
  status->status = coord_agent->InsertKeyValue(key, value);
}

// removal of the registration part from `Env` and adding it here instead: we
// will need tables to hold for each scheme the function tables that implement
// the needed functionality instead of the current `FileSystemRegistry` code in
// `core/platform/env.cc`.
class ModularFileSystem final : public FileSystem {
 public:
  ModularFileSystem(
      std::unique_ptr<TF_Filesystem> filesystem,

        "@com_google_absl//absl/strings",
        "@com_google_absl//absl/time",
        "@local_xla//xla/tsl/c:tsl_status_internal",
        "@local_xla//xla/tsl/distributed_runtime/coordination:coordination_service_agent",
    ],
    alwayslink = 1,
)

cc_library(
    name = "c_api_experimental_reader",
    testonly = True,
    srcs = [
        "c_api_experimental_reader.cc",
    ],
    hdrs = [

        which controls when the BFC Allocator needs to split an oversized chunk
        to satisfy an allocation request.
    *   Added `tf.get_current_name_scope()` which returns the current full name
        scope string that will be prepended to op names.
*   `tf.data`:
    *   Promoting `tf.data.experimental.bucket_by_sequence_length` API to

#
# This setting is currently experimental. The 'v2' implementation does _not_
# correspond to a particular, finalized design; rather, it relates to
# developing one.
#
# The current aim of the 'v2' implementation is to allow 'unused' ops and
# kernels to be discarded by the linker (to the benefit of binary size).
bool_flag(
    name = "enable_registration_v2",
    build_setting_default = False,

  # environment variables.
  environ_cp = dict(os.environ)

  try:
    current_bazel_version = retrieve_bazel_version()
  except subprocess.CalledProcessError as e:
    print('Error retrieving bazel version: ', e.output.decode('UTF-8').strip())
    raise e

  _TF_CURRENT_BAZEL_VERSION = convert_version_to_int(current_bazel_version)

  reset_tf_configure_bazelrc()

  cleanup_makefile()

# ==============================================================================

"""Import API packages test.

This is a Python test that verifies whether API v2 packages can be imported
from the current build or not.

It uses the `_api/v2/api_packages.txt` file from the local wheel file.
The `_api/v2/api_packages.txt` file is created during the process of generating

          minor_version=$(grep "^#define TF_MINOR_VERSION" ./tensorflow/core/public/version.h | grep -o "[[:digit:]]\+")
          echo "TF_VERSION=${major_version}.${minor_version}" >> "$GITHUB_OUTPUT"
          # Also get the current date to do cache busting. Assumes one day
          # is an ok range for rebuilds
          echo "DATE=$(date +'%Y-%m-%d')" >> "$GITHUB_OUTPUT"
        id: tf-version
      -
        name: Build and push

  in_grads.reserve(input_tensors.size());
  for (int target_index = 0; target_index < input_tensors.size();
       ++target_index) {
    const auto current_grad =
        accumulated_gradients_.find(input_tensors[target_index].GetID());
    if (current_grad == accumulated_gradients_.end()) {
      if (IsDtypeTrainable(input_tensors[target_index].GetDType())) {