to the actual TensorFlow wheel.
3. Creates a `requirements_lock_<python_version>.txt` file.
4. Updates the `requirements_lock_<python_version>.txt` file using
a Bazel command.
5. Moves the updated `requirements_lock_<python_version>.txt` file
to the `../wheel_test/` directory.


### How it Works in the Presubmit Job

`_requirements_lock` files will be generated by the presubmit job. A detailed

                  server_def_0, tensorflow::Env::Default(), &worker_server1)
                  .ok());
  ASSERT_TRUE(worker_server1->Start().ok());

  // 5a. Update `ctx_0` with updated `server_def_0`.
  {
    server_def_0.set_task_index(0);
    string serialized_update = server_def_0.SerializeAsString();
    TF_Status* status = TF_NewStatus();

                  server_def_0, tensorflow::Env::Default(), &worker_server1)
                  .ok());
  ASSERT_TRUE(worker_server1->Start().ok());

  // 5a. Update `ctx_0` with updated `server_def_0`.
  {
    server_def_0.set_task_index(0);
    string serialized_update = server_def_0.SerializeAsString();
    TF_Status* status = TF_NewStatus();

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

# script to run pip-compile for each requirement.
# if there is a change in requirements.in then all lock files will be updated
# accordingly

# All commands run relative to this directory
cd "$(dirname "${BASH_SOURCE[0]}")"

mv BUILD.bazel BUILD

SUPPORTED_VERSIONS=("3_9" "3_10" "3_11" "3_12")

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

# script to run pip-compile for keras, tensorboard, estimator deps.
# if there is a change in requirements.in then all lock files will be updated
# accordingly.

# -e: abort script if one command fails
# -u: error if undefined variable used
# -o pipefail: entire command fails if pipe fails. watch out for yes | ...
# -o history: record shell history

build --distinct_host_configuration=false

# Disable clang extension that rejects type definitions within offsetof. 
# This was added in clang-16 by https://reviews.llvm.org/D133574.
# Can be removed once upb is updated, since a type definition is used within
# offset of in the current version of ubp.
# See https://github.com/protocolbuffers/upb/blob/9effcbcb27f0a665f9f345030188c0b291e32482/upb/upb.c#L183.
build --copt=-Wno-gnu-offsetof-extensions

   `release_updater.sh`

5) Run the `updater.sh` shell script. \
   If the base requirements file hasn't yet been updated to account for the new
   Python version, which will require different versions for at least some
   dependencies, it will need to be updated now, for the script to run
   successfully.

6) A new `requirements_lock_3_11.txt` file should appear under the root of the

}

Status ImmediateExecutionTensorHandle::SummarizeValue(
    std::string& summary) const {
  Status status;
  AbstractTensorPtr resolved(
      // TODO(allenl): Resolve should be const, and the caches that get updated
      // marked mutable.
      const_cast<ImmediateExecutionTensorHandle*>(this)->Resolve(&status));
  if (!status.ok()) {
    return status;
  }
  summary = resolved->SummarizeValue();
  return absl::OkStatus();

# API IMPORTS PLACEHOLDER

# WRAPPER_PLACEHOLDER

if "dev" in __version__:   # pylint: disable=undefined-variable
  _logging.warning("""

  TensorFlow's `tf-nightly` package will soon be updated to TensorFlow 2.0.

  Please upgrade your code to TensorFlow 2.0:
    * https://www.tensorflow.org/guide/migrate

  Or install the latest stable TensorFlow 1.X release:
    * `pip install -U "tensorflow==1.*"`

// proto. Servers can be added to and removed from the list of remote workers
// in the context. A New set of servers identified by the ServerDef must be up
// when the context is updated.
//
// This API is for experimental usage and may be subject to change.
TF_CAPI_EXPORT extern void TFE_ContextUpdateServerDef(TFE_Context* ctx,
                                                      int keep_alive_secs,