// allows the caller to schedule computation on multiple ParallelDevices
  // without sequencing those operations (first call `StartExecute` on each
  // parallel device, then call `Join` on each; even if some of the `Join`s
  // return a bad status the caller must run all of the `Join`s or any future
  // `StartExecute`s will deadlock).
  //
  // If `is_async=false` (constructor argument), `cancellation_manager` must

       ++device_index) {
    DeviceThread* device_thread = device_threads_[device_index].get();
    per_device_output_tensors.push_back(device_thread->Join(status));
    // We will run every Join even if there are bad statuses in case the user
    // wants to recover and continue running ops on the parallel device (which
    // would otherwise deadlock).
    if (TF_GetCode(status) != TF_OK &&

// that defines two inputs, "concat_dim" and "values" (in that order).
// You must use TF_AddInput() for the first input (since it takes a
// single tensor), and TF_AddInputList() for the second input (since
// it takes a list, even if you were to pass a list with a single
// tensor), as in:
//   TF_OperationDescription* desc = TF_NewOperation(graph, "Concat", "c");
//   TF_Output concat_dim_input = {...};
//   TF_AddInput(desc, concat_dim_input);

 */

/** Get the domain of the user's email

  @param {!object}
    github enables querying for PR and also create issue using rest endpoint
    username has the login username of the Pull Request Event
  @return {string} Return the domain name of the user's email. Empty string if not found
*/

const get_email_domain = async ({github, username}) => {
  const user = await github.rest.users.getByUsername({
    username

  // threadpool, so that we avoid the possibility of running the runner_ in the
  // threadpool of GPU event mgr, as that can trigger more callbacks to be
  // scheduled on that same threadpool, causing a deadlock in cases where the
  // caller of event_mgr->ThenExecute() blocks on the completion of the callback
  // (as in the case of ConstOp kernel creation on GPU, which involves copying a

//tensorflow/python/kernel_tests/signal
//tensorflow/examples
//tensorflow/tools/android
//tensorflow/python/eager/benchmarks
EOF

  # grep patterns for files and targets which don't need to be in the pip
  # package, ever.
  cat > $BATS_TEST_TMPDIR/ignore_these_deps <<EOF
benchmark
_test$
_test.py$
_test_cpu$
_test_cpu.py$
_test_gpu$
_test_gpu.py$
_test_lib$
//tensorflow/cc/saved_model:saved_model_test_files

build:rbe_cross_compile_macos_x86 --config=cross_compile_macos_x86 --remote_download_minimal
build:rbe_cross_compile_macos_x86 --bes_backend="" --bes_results_url="" --bes_timeout="0s"
build:rbe_cross_compile_macos_x86 --experimental_remote_build_event_upload="minimal"
build:rbe_cross_compile_macos_x86 --config=rbe_cross_compile_base
build:rbe_cross_compile_macos_x86 --bes_upload_mode=nowait_for_upload_complete
test:rbe_cross_compile_macos_x86 --config=rbe_cross_compile_base