*
     * @param first the first provider to combine with
     * @param second the second provider to combine with
     * @param combiner the combiner of values. May return {@code null}, in which case the provider
     * will have no value.
     * @param <A> the type of the first provider
     * @param <B> the type of the second provider
     * @param <R> the type of the result of the combiner
     * @return a combined provider

                throw UncheckedException.throwAsUncheckedException(t);
            } else {
                // Created a result which may contain failures. Combine this failure with any failures that happen to be packaged in the result

                throw UncheckedException.throwAsUncheckedException(t);
            } else {
                // Cleanup has failed, combine the cleanup failure with other failures that may be packed in the result

  ASSERT_FALSE(shape.unknown_rank());

  ASSERT_EQ(2, shape.dim_size(0));
  ASSERT_EQ(-1, shape.dim_size(1));
}

INSTANTIATE_TEST_SUITE_P(
    UnifiedCppAPI, UnifiedAPI,
    ::testing::Combine(::testing::Values("graphdef", "mlir"),
                       /*tfrt*/ ::testing::Values(false),
                       /*use_function*/ ::testing::Values(true, false)));
}  // namespace

</blockquote>

## Investigation

By using all the previous alternatives I had the chance to learn from all of them, take ideas, and combine them in the best way I could find for myself and the teams of developers I have worked with.

For example, it was clear that ideally it should be based on standard Python type hints.

```

Tout sera combiné et inclus dans votre OpenAPI, et affiché dans la documentation de l'API :

<img src="/img/tutorial/additional-responses/image01.png">

## Combinez les réponses prédéfinies et les réponses personnalisées

      return errors::Internal("Unknown dimension size in constant tensor ",
                              n->name());
    }
    total_elements *= dim.size();
  }

  // TODO(sanjoy): It may make sense to combine this threshold with XLA's "large
  // constant" threshold, if there is one.
  const int kSmallTensorThreshold = 16;
  return total_elements < kSmallTensorThreshold;
}

    @Override
    public Builder<E> addAll(Iterator<? extends E> elements) {
      super.addAll(elements);
      return this;
    }

    @CanIgnoreReturnValue
    Builder<E> combine(Builder<E> builder) {
      super.combine(builder);
      return this;
    }

    @Override
    public ImmutableSortedSet<E> build() {
      return copyOfInternal(comparator, contents.iterator());
    }
  }

      }
  }

  for (sectionList in result.values) {
    mergeAdjacentDeltaMappedRanges(sectionList)
  }

  return result.toMap()
}

/**
 * Modifies [ranges] to combine any adjacent [MappedRange.InlineDelta] of same size to single entry.
 * @returns same instance of [ranges] for convenience
 */

        // When this classloader is reused for multiple requests, the classpath of subsequent requests may be different.
        // So, update the classpath of this shared classloader
        // It would be better to not combine client classloaders but instead to recreate the client side structure
        if (details.spec instanceof ClientOwnedClassLoaderSpec) {
            ClientOwnedClassLoaderSpec spec = (ClientOwnedClassLoaderSpec) details.spec;