namespace tensorflow {

// Set the shapes and types of the output's handle.
//
// The lengths of the arrays pointed to by `shapes`, `ranks`, and `types` must
// all be equal to `num_shapes_and_types`. If `ranks[i] != -1`, (i.e., if the
// rank is known), then it must be equal to the length of `shapes[i]`; if
// `ranks[i] == 1`, then `shapes[i]` may be nullptr.
//

 public:
  CheckpointReader(const std::string& filename, TF_Status* status);

  bool HasTensor(const std::string& name) const;
  const std::string DebugString() const;

  // Returns a map from variable names to their shapes.  Slices of a partitioned
  // tensor are combined into a single entry.
  const TensorSliceReader::VarToShapeMap& GetVariableToShapeMap() const;

  // Returns a map from variable names to their data types.  Slices of a

*   Tracing/timeline support for distributed runtime (no GPU profiler yet).
*   C API gives access to inferred shapes with `TF_GraphGetTensorNumDims` and
    `TF_GraphGetTensorShape`.
*   Shape functions for core ops have moved to C++ via
    `REGISTER_OP(...).SetShapeFn(...)`. Python shape inference RegisterShape
    calls use the C++ shape functions with `common_shapes.call_cpp_shape_fn`. A
    future release will remove `RegisterShape` from python.

        assertFalse(sentPrompt.contains("{{conversationHistory}}"));
    }

    // ========== History content mode pattern tests ==========
    // These test the different history shapes that extractHistory() produces
    // depending on rag.chat.history.assistant.content mode (full, source_titles,
    // source_titles_and_urls, truncated, none).

    @Test

TEST_F(CApiAttributesTest, ShapeList) {
  const int64_t shape_1[] = {1, 3};
  const int64_t shape_2[] = {2, 4, 6};
  const int64_t* list[] = {&shape_1[0], &shape_2[0]};
  const size_t list_size = TF_ARRAYSIZE(list);
  const int ndims[] = {TF_ARRAYSIZE(shape_1), TF_ARRAYSIZE(shape_2)};
  const int total_ndims = 5;  // ndims[0] + ndims[1]

  auto desc = init("list(shape)");
  TF_SetAttrShapeList(desc, "v", list, ndims, list_size);

Для цього використовуємо `security_scopes.scopes`, що містить `list` із усіма цими scopes як `str`.

{* ../../docs_src/security/tutorial005_an_py310.py hl[130:136] *}

## Дерево залежностей і scopes { #dependency-tree-and-scopes }

Ще раз розгляньмо дерево залежностей і scopes.

                            * *Path operation* `read_system_status` için `security_scopes.scopes` `[]` (boş) olur; çünkü herhangi bir `Security` ile `scopes` tanımlamamıştır ve dependency'si olan `get_current_user` da `scopes` tanımlamaz.

/// tip | İpucu

Buradaki önemli ve "sihirli" nokta şu: `get_current_user`, her *path operation* için kontrol etmesi gereken farklı bir `scopes` listesi alır.

/// tip | Dica

A coisa importante e "mágica" aqui é que `get_current_user` terá diferentes listas de `scopes` para validar para cada *operação de rota*.

Nevertheless, you still enforce those scopes, or any other security/authorization requirement, however you need, in your code.

In many cases, OAuth2 with scopes can be an overkill.

But if you know you need it, or you are curious, keep reading.

///

## OAuth2 scopes and OpenAPI { #oauth2-scopes-and-openapi }

## Die `scopes` verifizieren { #verify-the-scopes }

Wir überprüfen nun, ob das empfangene Token alle Scopes enthält, die von dieser Abhängigkeit und deren Verwendern (einschließlich *Pfadoperationen*) gefordert werden. Andernfalls lösen wir eine `HTTPException` aus.

Hierzu verwenden wir `security_scopes.scopes`, das eine `list`e mit allen diesen Scopes als `str` enthält.