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

permissions:
  contents: read

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:

        scheme: str,
        scheme_name: Optional[str] = None,
        description: Optional[str] = None,
        auto_error: bool = True,
    ):
        self.model = HTTPBaseModel(scheme=scheme, description=description)
        self.scheme_name = scheme_name or self.__class__.__name__
        self.auto_error = auto_error

    async def __call__(
        self, request: Request
    ) -> Optional[HTTPAuthorizationCredentials]:

        )
        self.scheme_name = scheme_name or self.__class__.__name__
        self.auto_error = auto_error

    async def __call__(self, request: Request) -> Optional[str]:
        api_key = request.query_params.get(self.model.name)
        if not api_key:
            if self.auto_error:
                raise HTTPException(
                    status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"

        )
        self.scheme_name = scheme_name or self.__class__.__name__
        self.auto_error = auto_error

    async def __call__(self, request: Request) -> Optional[str]:
        authorization = request.headers.get("Authorization")
        if not authorization:
            if self.auto_error:
                raise HTTPException(
                    status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"

    void (*delete_func)(void*), TF_Status* status) {
  auto* cc_ctx = reinterpret_cast<tensorflow::OpKernelContext*>(ctx);
  auto* resource_mgr = cc_ctx->resource_manager();
  tensorflow::core::RefCountPtr<tensorflow::PluginResource>
      tf_plugin_resource_ptr;
  tensorflow::PluginResource* tf_plugin_resource = nullptr;

  auto cc_status = resource_mgr->LookupOrCreate<tensorflow::PluginResource>(

    @Override
    public DBDef assistCurrentDBDef() {
        // TODO Auto-generated method stub
        return null;
    }

    @Override
    public DataSource assistDataSource() {
        // TODO Auto-generated method stub
        return null;
    }

    @Override
    public DBMetaProvider assistDBMetaProvider() {
        // TODO Auto-generated method stub
        return null;
    }

    @Override

    int64_t op_id = op_id_it->second;
    auto op_it = op_tape->find(op_id);
    auto result_op_it = result.op_tape.find(op_id);
    if (op_id == -1 || op_it == op_tape->end() ||
        result_op_it != result.op_tape.end()) {
      continue;
    }
    CHECK(result.op_tape.emplace(op_id, op_it->second).second);
    for (auto it : op_it->second.input_tensor_id) {
      auto count_it = result.tensor_usage_counts.find(it);

  TF_Tensor* analytical_tensor;
  auto s = GetValue(t, &analytical_tensor);
  ASSERT_EQ(errors::OK, s.code()) << s.message();

  int64_t num_elem_analytical = 1;
  auto num_dims_analytical = TF_NumDims(analytical_tensor);
  ASSERT_EQ(dims.size(), num_dims_analytical);
  for (int j = 0; j < num_dims_analytical; j++) {
    auto dim_analytical = TF_Dim(analytical_tensor, j);

  return new TFE_Executor(&tensorflow::unwrap(ctx)->Executor());
}

void TFE_HostAddressSpace(TFE_Context* ctx, TF_Buffer* buf) {
  auto address_space = tensorflow::DeviceNameUtils::AddressSpace(
      tensorflow::unwrap(ctx)->HostCPUParsedName());
  auto str = tensorflow::DeviceNameUtils::ParsedNameToString(address_space);
  void* data = tensorflow::port::Malloc(str.length());

        )
        self.scheme_name = scheme_name or self.__class__.__name__
        self.auto_error = auto_error

    async def __call__(self, request: Request) -> Optional[str]:
        authorization = request.headers.get("Authorization")
        if not authorization:
            if self.auto_error:
                raise HTTPException(
                    status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"