// can do its work.
    //
    // Rather than re-entering and delegating Accumulate like this, we could
    // instead allow ForwardAccumulator some control over the current tape set
    // (so it can deactivate itself and activate its GradientTape). Currently
    // that is managed by the language binding and would require relatively
    // messy callbacks.
    call_state_.top().backward_tape->RecordOperation(

//
// Otherwise, while traversing the tree, undeleted_file_count and
// undeleted_dir_count are updated if an entry of the corresponding type could
// not be deleted. The returned error status represents the reason that any one
// of these entries could not be deleted.
//
// Typical status codes:
//  * TF_OK - dirname exists and we were able to delete everything underneath
//  * TF_NOT_FOUND - dirname doesn't exist

  if get_var(
      environ_cp, 'TF_OVERRIDE_EIGEN_STRONG_INLINE', 'Eigen strong inline',
      True, ('Would you like to override eigen strong inline for some C++ '
             'compilation to reduce the compilation time?'),
      'Eigen strong inline overridden.', 'Not overriding eigen strong inline, '
      'some compilations could take more than 20 mins.'):
    # Due to a known MSVC compiler issue

setup_file() {
    cd /tf/tensorflow
    bazel version  # Start the bazel server
    # Without this, git errors if /tf/tensorflow directory owner is different
    git config --global --add safe.directory /tf/tensorflow
    # Note that you could generate a list of all the affected targets with e.g.:
    # bazel query $(paste -sd "+" $BATS_FILE_TMPDIR/changed_files) --keep_going
    # Only shows Added, Changed, Modified, Renamed, and Type-changed files

#               (affects 'source $TFCI')
set -euxo pipefail -o history -o allexport

# Set TFCI_GIT_DIR, the root directory for all commands, to two directories
# above the location of this file (setup.sh). We could also use "git rev-parse
# --show-toplevel", but that wouldn't work for non-git repos (like if someone
# downloaded TF as a zip archive).
export TFCI_GIT_DIR=$(cd $(dirname "$0"); realpath ../../)
cd "$TFCI_GIT_DIR"

  return nullptr;
#else
  tensorflow::ServerDef server_def;
  if (!server_def.ParseFromArray(proto, static_cast<int>(proto_len))) {
    status->status = InvalidArgument(
        "Could not parse provided bytes into a ServerDef protocol buffer");
    return nullptr;
  }

  std::unique_ptr<tensorflow::ServerInterface> out_server;
  status->status = tensorflow::NewServer(server_def, &out_server);

  /// and `*undeleted_dirs` must be 0. On unsuccessful deletion, `status` must
  /// be set to the reason why one entry couldn't be removed and the proper
  /// count must be updated. If the deletion is unsuccessful because the
  /// traversal couldn't start, `*undeleted_files` must be set to 0 and
  /// `*undeleted_dirs` must be set to 1.
  ///

        -  It could also be a simple python or TF utility that you could easily copy over to your own codebase. In those case, just make it your own!
        -  If you believe it should definitely be a public Keras API, please open a feature request in keras GitHub repo.

              delete reinterpret_cast<DataType*>(data);
            },
            nullptr),
        TF_DeleteTensor);
    // TODO(allenl): Here and when executing regular operations, we could hold
    // on to one TFE_Op per device and just call TFE_ResetOp to avoid parsing
    // device names repeatedly.
    std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> const_op(

the problem. If possible, please share a link to or attach code demonstrating
the problem.

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