// 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();
}

# 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

    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]);
    }
  }

    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

    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) {

    TFE_TensorHandle* input_eager = TestScalarTensorHandle(eager_ctx, 2.0f);
    func_args.push_back(TF_CreateAbstractTensorFromEagerTensor(input_eager, s));
    ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
    input_eager = TestScalarTensorHandle(eager_ctx, 3.0f);
    func_args.push_back(TF_CreateAbstractTensorFromEagerTensor(input_eager, s));
    ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  }

    std::uniform_int_distribution<> distribution;
    rng_val_ = distribution(gen);
  }

  static void SetCloudPath(const std::string& cloud_path) {
    cloud_path_ = cloud_path;
    if (cloud_path_.back() == '/') cloud_path_.pop_back();
  }

  static void SetTmpDir(const std::string& tmp_dir) {
    tmp_dir_ = tmp_dir.empty() ? ::testing::TempDir() : tmp_dir;
  }

 protected:
  Env* env_;

 private:

    TFE_OpAddInput(op, h, status);
    ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);

    std::vector<TFE_TensorHandle*> result;
    result.push_back(nullptr);
    int num_retvals = 1;
    TFE_Execute(op, result.data(), &num_retvals, status);
    TFE_DeleteOp(op);
    ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
    ASSERT_EQ(num_retvals, 1);

    if (TF_GetCode(status.get()) != TF_OK) {
      ADD_FAILURE() << tag << " -- " << TF_Message(status.get());
      continue;
    }
    TFE_DeleteTensorHandle(hdevice);
    // Copy back to CPU
    TFE_TensorHandle* hcopy =
        TFE_TensorHandleCopyToDevice(hdevice2, ctx, kCPUDevice, status.get());
    if (TF_GetCode(status.get()) != TF_OK) {
      ADD_FAILURE() << tag << " -- " << TF_Message(status.get());