// Assign to PR owner and reviewers
  const assignees = pr_resp.data.assignees.concat(pr_resp.data.requested_reviewers);
  let assignee_logins = assignees.map(x => x.login);
  assignee_logins.push(pr_resp.data.user.login);
  console.log(assignee_logins);
  // Create an new GH Issue and reference the Original PR
  const resp = await github.rest.issues.create({
    owner,
    repo,
    assignees: assignee_logins,

# limitations under the License.
# ============================================================================

# A list of assignees
assignees:
   - sushreebarsa
   - SuryanarayanaY
   - tilakrayal
   - Venkat6871
# A list of assignees for compiler folder
compiler_assignees:
   - joker-eph
   - sanjoy
# filesystem path
filesystem_path:
   - tensorflow/c/experimental/filesystem
# security path

    assignees = intel_windows_assignees;
  const apple_silicon_assignees = ['penpornk', 'nitins17'];
  if (lowercased_title.includes('apple') &&
      lowercased_title.includes('silicon') && domain.includes('apple.com'))
    assignees = apple_silicon_assignees;
  if (lowercased_title.includes('tf-trt') && domain.includes('nvidia.com')) {
    assignees.push(

If you have improvements to TensorFlow, send us your pull requests! For those
just getting started, GitHub has a
[how-to](https://help.github.com/articles/using-pull-requests/).

TensorFlow team members will be assigned to review your pull requests. Once the
pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are

// a map (`tensorflow::eager::TensorTape`) from the wrapped tensor to the id of
// the op that produced it (or -1 if this tensor was watched using
// `GradientTape::Watch`.) The op_id is simply a unique index assigned to each
// op executed under the tape. A separate map (`tensorflow::eager::OpTape`)
// maintains the map from `op_id` to a `OpTapeEntry` which stores the `op_type`,

    TF_LOCKS_EXCLUDED(session->graph->mu, session->mu);

std::string getTF_OutputDebugString(TF_Output node);

// Set whether to propagate assigned device information when constructing a new
// Graph from a GraphDef. By default assigned device information is not copied
// and is re-computed by the runtime.
inline void TF_ImportGraphDefOptionsSetPropagateDeviceSpec(

        values every time they are called (for a given variable shape). For
        unseeded initializers (`seed=None`), a random seed will be created and
        assigned at initializer creation (different initializer instances get
        different seeds).
    *   An unseeded initializer will raise a warning if it is reused (called)

        uses: actions/stale@6f05e4244c9a0b2ed3401882b05d701dd0a7289b # v7.0.0
        with:
          #Comma separated list of labels that can be assigned to issues to exclude them from being marked as stale
          exempt-issue-labels: 'override-stale'
          #Comma separated list of labels that can be assigned to PRs to exclude them from being marked as stale
          exempt-pr-labels: "override-stale"