// fetcher calls that the cache makes.
  calls.push_back(0);
  // Cache miss - drains an element from `calls`.
  TF_EXPECT_OK(ReadCache(&cache, "", 0, 1, &out));
  // Cache hit - does not drain an element from `calls`.
  TF_EXPECT_OK(ReadCache(&cache, "", 0, 1, &out));
  calls.push_back(block_size);
  // Cache miss followed by cache hit.

  TF_RETURN_IF_ERROR(parent_op_->AddInput(input));
  forward_op_.inputs.push_back(input);
  return OkStatus();
}
Status TapeOperation::AddInputList(
    absl::Span<AbstractTensorHandle* const> inputs) {
  TF_RETURN_IF_ERROR(parent_op_->AddInputList(inputs));
  for (auto input : inputs) {
    forward_op_.inputs.push_back(input);
  }
  return OkStatus();
}

    plugin_status.reserve(files.size());
    for (int i = 0; i < files.size(); i++)
      plugin_status.push_back(TF_NewStatus());
    result = ops_->paths_exist(filesystem_.get(), translated_names.data(),
                               files.size(), plugin_status.data());
    for (int i = 0; i < files.size(); i++) {
      status->push_back(StatusFromTF_Status(plugin_status[i]));
      TF_DeleteStatus(plugin_status[i]);
    }
  }

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

name: Creates a GitHub Issue when a PR Rolled back via Commit to Master
on:
  push:
    branches:
      - master
      
permissions: {}

jobs:
  create-issue-on-pr-rollback:
    runs-on: ubuntu-latest
    permissions:
      contents: read

    absl::MutexLock lock(&mu_);
    uint64_t now = timer_seconds_();
    while (!lra_list_.empty()) {
      auto it = block_map_.find(lra_list_.back());
      if (now - it->second->timestamp <= max_staleness_) {
        // The oldest block is not yet expired. Come back later.
        break;
      }
      // We need to make a copy of the filename here, since it could otherwise

  opts->opts.control_dependencies.push_back(oper->node.name());
}

void TF_ImportGraphDefOptionsAddReturnOutput(TF_ImportGraphDefOptions* opts,
                                             const char* oper_name, int index) {
  opts->tensor_id_data.push_back(oper_name);
  const string& oper_name_str = opts->tensor_id_data.back();
  opts->opts.return_tensors.emplace_back(oper_name_str, index);
}

  std::vector<const char*> raw_strs;
  std::vector<size_t> lengths;
  raw_strs.reserve(values.size());
  lengths.reserve(values.size());
  for (const auto& s : values) {
    raw_strs.emplace_back(s.data());
    lengths.emplace_back(s.size());
  }
  return SetAttrStringList(attr_name,
                           reinterpret_cast<const void**>(raw_strs.data()),
                           lengths.data(), values.size());
}

    return shape;
  }
  shape.reserve(rank);
  for (int i = 0; i < rank; ++i) {
    int64_t dim;
    *status = handle.Dim(i, &dim);
    if (!status->ok()) {
      return shape;
    }
    shape.push_back(dim);
  }
  return shape;
}

}  // namespace

extern "C" {

TF_CAPI_EXPORT extern TFE_TensorDebugInfo* TFE_TensorHandleTensorDebugInfo(
    TFE_TensorHandle* h, TF_Status* status) {

        return result;
      }
      components.emplace_back(TFE_TensorHandleCopySharingTensor(
          absl::get<TFE_TensorHandle*>(inputs[i]), status));
    }
    std::vector<MaybeParallelTensorOwned> result_content;
    result_content.reserve(1);
    result_content.push_back(ParallelTensor::FromTensorHandles(
        parallel_device, std::move(components), status));

    components.reserve(underlying_devices_.size());
    for (int j = 0; j < underlying_devices_.size(); ++j) {
      components.push_back(std::move(per_device_output_tensors[j][i]));
    }
    if (expected_output_shapes[i].IsFullyDefined()) {
      per_device_outputs.push_back(ParallelTensor::FromTensorHandles(
          *this, std::move(components),
          absl::Span<const int64_t>(expected_output_shapes[i].dim_sizes()),