p1, p2 = p2, p1
	}

	// The lowest common ancestor is the minimum depth block
	// on the tour from p1 to p2.  We've precomputed minimum
	// depth blocks for powers-of-two subsequences of the tour.
	// Combine the right two precomputed values to get the answer.
	logS := uint(log64(int64(p2 - p1)))
	bid1 := lca.rangeMin[logS][p1]
	bid2 := lca.rangeMin[logS][p2-1<<logS+1]
	if lca.blocks[bid1].depth < lca.blocks[bid2].depth {

	if err != nil {
		return nil, &FormatError{offset, "invalid fat_header", nil}
	}
	offset += 4

	if narch < 1 {
		return nil, &FormatError{offset, "file contains no images", nil}
	}

	// Combine the Cpu and SubCpu (both uint32) into a uint64 to make sure
	// there are not duplicate architectures.
	seenArches := make(map[uint64]bool)
	// Make sure that all images are for the same MH_ type.
	var machoType Type

  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

type MergeErrorType string

const (
	// CannotFetchProfileError occurs when profile cannot be found.
	CannotFetchProfileError MergeErrorType = "cannot_fetch_profile"

	// OverlayError overlaying YAMLs to combine profile, user
	// defined settings in CR, Hub-tag etc. fails.
	OverlayError MergeErrorType = "overlay"

	// IOPFormatError occurs when supplied CR cannot be marshaled
	// or unmarshaled to/from YAML.

      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());
    }
  }

	// Loads or stores larger than Alignment need only be Alignment-aligned.
	Alignment int8

	// CanMergeLoads reports whether the backend optimization passes
	// can combine adjacent loads into a single larger, possibly unaligned, load.
	// Note that currently the optimizations must be able to handle little endian byte order.
	CanMergeLoads bool

     * queried. The file tree is also live, so that it scans for files each time the contents of the file tree are
     * queried.
     *
     * You can combine this method with the [copy] method to unzip a ZIP file.
     *
     * @param zipPath The ZIP file. Evaluated as per [file].
     * @return The file tree.
     */
    fun zipTree(zipPath: Any): FileTree

    /**