name: 'Auto Assign PR to Author'
on:
  pull_request:
    types: [opened]

permissions: {}

jobs:
  add-reviews:
    permissions:
      contents: read  # for kentaro-m/auto-assign-action to fetch config file
      pull-requests: write  # for kentaro-m/auto-assign-action to assign PR reviewers
    runs-on: ubuntu-latest
    steps:

    @Test
    public void test_init_nofile() {
        ComponentUtil.setFessConfig(new FessConfig.SimpleImpl() {
            @Override
            public String getOsddLinkEnabled() {
                return "auto";
            }

            @Override
            public String getSsoType() {
                return "none";
            }
        });
        final OsddHelper osddHelper = new OsddHelper();

        // Get explicit type or auto-detect
        final String typeStr = fessConfig.getStorageType();
        final StorageType type;
        if (StringUtil.isBlank(typeStr) || "auto".equalsIgnoreCase(typeStr)) {
            type = detectStorageType(endpoint);
            if (logger.isDebugEnabled()) {
                logger.debug("Auto-detected storage type: {} for endpoint: {}", type, endpoint);
            }

  StringVectorToArrays(list, &list_ptrs, &list_lens);
  int list_total_size = 0;
  for (const auto& s : list) {
    list_total_size += s.size();
  }

  auto desc = init("list(string)");
  TF_SetAttrStringList(desc, "v", list_ptrs.get(), list_lens.get(),
                       list.size());

  auto oper = TF_FinishOperation(desc, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  if (TF_GetCode(s) != TF_OK) return;
  std::vector<TFE_TensorHandle*> unwrapped_outputs;
  unwrapped_outputs.reserve(op_outputs.size());
  for (auto* handle : op_outputs) {
    unwrapped_outputs.push_back(handle);
  }
  for (int i = 0; i < *num_outputs; ++i) {
    auto logged_tensor = std::make_unique<LoggedTensor>(unwrapped_outputs[i]);
    outputs[i] = MakeLoggedTensorHandle(context, dev->device_name,

          if git diff --staged --quiet; then
            echo "No changes to commit"
          else
            git commit -m "🎨 Auto format"
            git push
          fi
      - uses: pre-commit-ci/lite-action@v1.1.0
        if: env.HAS_SECRETS == 'false'
        with:
          msg: 🎨 Auto format
      - name: Error out on pre-commit errors
        if: steps.precommit.outcome == 'failure'
        run: exit 1

  *result = outputs[0];
  return absl::OkStatus();
}
}  // namespace

absl::Status GradientRegistry::Register(
    const string& op_name, GradientFunctionFactory gradient_function_factory) {
  auto iter = registry_.find(op_name);
  if (iter != registry_.end()) {
    return absl::AlreadyExistsError(
        absl::StrCat("Gradient already exists for op: ", op_name, "."));
  }

//
// The code under test will have created streamz counters like this:
// auto* streamz = tensorflow::monitoring::Counter<1>::New("name",
// "description", "label");
// and then incremented that counter for various values of label:
// streamz->GetCell("label-value")->IncrementBy(1);
//
// The test code can then read and test the value of that counter:
//
// auto* reader = TFE_MonitoringNewCounterReader("name");
// test();

# Define this here and not in the main mkdocs.yml file because that one is auto
# updated and written, and the script would remove the env var
markdown_extensions:
  pymdownx.highlight:

}

func TestManyToManyWithMultiPrimaryKeys(t *testing.T) {
	if name := DB.Dialector.Name(); name == "sqlite" || name == "sqlserver" {
		t.Skip("skip sqlite, sqlserver due to it doesn't support multiple primary keys with auto increment")
	}

	if name := DB.Dialector.Name(); name == "postgres" || name == "mysql" || name == "gaussdb" {
		stmt := gorm.Statement{DB: DB}
		stmt.Parse(&Blog{})
		stmt.Schema.LookUpField("ID").Unique = true