.get());
            options.addOption(Option.builder(INFER)
                    .longOpt("infer")
                    .desc("Use inference when upgrading (remove redundant information)")
                    .get());
            options.addOption(Option.builder(MODEL)
                    .longOpt("model")

Toutes les conversions de données, validations, documentation, etc., fonctionneront comme d'habitude.

De cette façon, nous pouvons ne déclarer que les différences entre les modèles (avec `password` en clair, avec `hashed_password` et sans mot de passe) :

{* ../../docs_src/extra_models/tutorial002_py310.py hl[7,13:14,17:18,21:22] *}

## `Union` ou `anyOf` { #union-or-anyof }

    validations:
      required: true

  - type: markdown
    attributes:
      value: >
        Comparing two approaches to a use case side by side can make it easier to examine the
        differences between them.


        Additionally, it's very useful to us if you can provide a "straw API" — what the
        method signatures would look like, for example, even if the method and class names are still

struct TF_Library {
  void* lib_handle;
  TF_Buffer op_list;
};

struct TF_Graph {
  TF_Graph();

  mutable tensorflow::mutex mu;
  tensorflow::Graph graph TF_GUARDED_BY(mu);

  // Runs shape inference.
  tensorflow::ShapeRefiner refiner TF_GUARDED_BY(mu);

  // Maps from name of an operation to the Node* in 'graph'.
  std::unordered_map<std::string, tensorflow::Node*> name_map TF_GUARDED_BY(mu);

The MinIO Security Token Service (STS) is an endpoint service that enables clients to request temporary credentials for MinIO resources. Temporary credentials work almost identically to default admin credentials, with some differences:

              getLowerEndpoint(),
              getLowerBoundType());
      result.reverse = this;
      return this.reverse = result;
    }
    return result;
  }

  // This method helps J2KT's type inference.
  private static <T extends @Nullable Object> Comparator<T> reverseComparator(
      Comparator<T> comparator) {
    return Ordering.from(comparator).reverse();
  }

  @Override
  public String toString() {

  }

  ~ShapeInferenceTest() override {
    TFE_DeleteContextOptions(tfe_context_options_);
    TFE_DeleteContext(tfe_context_);
    TF_DeleteStatus(status_);
  }

  // Checks the expected result of shape inference for the given `op`.
  void CheckOutputShapes(
      TFE_Op* op,
      const std::vector<absl::optional<std::vector<int64_t>>>& input_shapes_vec,
      const std::vector<TF_Tensor*>& input_tensors,

All the data conversion, validation, documentation, etc. will still work as normally.

That way, we can declare just the differences between the models (with plaintext `password`, with `hashed_password` and without password):

{* ../../docs_src/extra_models/tutorial002_py310.py hl[7,13:14,17:18,21:22] *}

## `Union` or `anyOf` { #union-or-anyof }

  @Override
  public int hashCode() {
    return Sets.hashCodeImpl(this);
  }

  // This declaration is needed to make Set.iterator() and
  // ImmutableCollection.iterator() appear consistent to javac's type inference.
  @Override
  public abstract UnmodifiableIterator<E> iterator();

  abstract static class CachingAsList<E> extends ImmutableSet<E> {
    @LazyInit private transient ImmutableList<E> asList;

    @Override

- Server-side encryption - The Select API supports querying objects that are protected with server-side encryption.

Type inference and automatic conversion of values is performed based on the context when the value is un-typed (such as when reading CSV data). If present, the CAST function overrides automatic conversion.