}

// CombinedAnalyzer is an interface used to combine and run multiple analyzers into one
type CombinedAnalyzer interface {
	Analyzer
	RelevantSubset(kinds sets.Set[config.GroupVersionKind]) CombinedAnalyzer
	RemoveSkipped(schemas collection.Schemas) []string
	AnalyzerNames() []string
}

// InternalCombinedAnalyzer is an implementation of CombinedAnalyzer, a special analyzer that combines multiple analyzers into one

John Howard <******@****.***> 1713303040 -0700

```

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

			if cccB == 0 {
				s = k - 1
			} else {
				blocked = s != k-1 && cccB >= cccC
			}
			if !blocked {
				combined := combine(rb.runeAt(s), rb.runeAt(i))
				if combined != 0 {
					rb.assignRune(s, combined)
					continue
				}
			}
		}
		b[k] = b[i]
		k++
	}
	rb.nrune = k

// Note that the recomposition map for NFC and NFKC are identical.

// combine returns the combined rune or 0 if it doesn't exist.
//
// The caller is responsible for calling
// recompMapOnce.Do(buildRecompMap) sometime before this is called.
func combine(a, b rune) rune {
	key := uint32(uint16(a))<<16 + uint32(uint16(b))
	if recompMap == nil {

   */
  public static <V1 extends @Nullable Object, V2 extends @Nullable Object>
      Combiner2<V1, V2> whenAllSucceed(ClosingFuture<V1> future1, ClosingFuture<V2> future2) {
    return new Combiner2<>(future1, future2);
  }

  /**
   * Starts specifying how to combine three {@link ClosingFuture}s into a single pipeline, assuming
   * they all succeed. If any fail, the resulting pipeline will fail.

	}
	return analyzers
}

// AllCombined returns all analyzers combined as one
func AllCombined() analysis.CombinedAnalyzer {
	return analysis.Combine("all", All()...)
}

// AllMultiClusterCombined returns all multi-cluster analyzers combined as one
func AllMultiClusterCombined() analysis.CombinedAnalyzer {
	return analysis.Combine("all-multi-cluster", AllMultiCluster()...)

     *
     * @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

     * </p>
     *
     * @param right 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 <U> the type of the second provider
     * @param <R> the type of the result of the combiner
     * @return a combined provider
     * @since 6.6
     */

    %zp_offset: tensor<?x2x2x1xi32>, %bias: tensor<1xi32>
  ) -> tensor<?x2x2x1xi32> {
  // CHECK-DAG: %[[conv:.*]] = mhlo.convolution
  // CHECK-DAG: %[[combined:.*]] = chlo.broadcast_add %[[zp_offset:.*]], %[[bias:.*]]
  // CHECK-DAG: %[[result:.*]] = chlo.broadcast_add %[[conv]], %[[combined]]
  // CHECK: return %[[result]]
  %0 = mhlo.convolution(%lhs, %rhs)
      dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f],