var best bitmask.BitMask
		if (policyName != PolicySingleNumaNode) && opts.PreferClosestNUMA {
			best = numaInfo.Closest(current.NUMANodeAffinity, candidate.NUMANodeAffinity)
		} else {
			best = numaInfo.Narrowest(current.NUMANodeAffinity, candidate.NUMANodeAffinity)
		}
		if best.IsEqual(current.NUMANodeAffinity) {
			return current
		}
		return candidate
	}

	merger := HintMerger{

[[sub:terminology_dependency_constraint]]
== Dependency constraint

A dependency constraint defines requirements that need to be met by a module to make it a valid resolution result for the dependency.
For example, a dependency constraint can narrow down the set of supported module versions.
Dependency constraints can be used to express such requirements for transitive dependencies.

      // The initial quantization is used someplace else ... so it might be
      // reasonable for it to requantized for another purpose.
      // Ideally would want to still check whether requantization narrows
      // rather than widens the representation.
      return;
    }

    // Invariant:
    // isa<quantfork::QuantizeCastOp>(dq_arg.getDefiningOp()) -->
    // getdq_arg.getType() != q_op.getResult().getType()

      // The initial quantization is used someplace else ... so it might be
      // reasonable for it to requantized for another purpose.
      // Ideally would want to still check whether requantization narrows
      // rather than widens the representation.
      return;
    }

    // Invariant:
    // isa<quantfork::QuantizeCastOp>(dq_arg.getDefiningOp()) -->
    // getdq_arg.getType() != q_op.getResult().getType()

	klog.Infof("Starting cluster_authentication_trust_controller controller")
	defer klog.Infof("Shutting down cluster_authentication_trust_controller controller")

	// we have a personal informer that is narrowly scoped, start it.
	go c.kubeSystemConfigMapInformer.Run(ctx.Done())

	// wait for your secondary caches to fill before starting your work

	// If we aren't allowed to build sets of size 2+N, give up this branch.
	if b.MaxSet > 0 && 2+len(b.Add) > b.MaxSet {
		return nil
	}

	// Adding all matches for 1suffix, recurse to narrow down 0suffix.
	old := len(b.Add)
	b.Add = append(b.Add, "1"+suffix)
	r0 = b.Run("0" + suffix)
	if r0.Success {
		// 0suffix + b.Add + 1suffix = suffix + b.Add is what r describes, and it failed.

      return absl::InvalidArgumentError(
          "Quantized tensors must be stored as integers");
    }
    storage_type = mlir::cast<mlir::IntegerType>(raw_elem_type);
  }

  // TFlite uses narrow-range [u]int8 for constant buffers of quantized weights.
  // Since we don't know which ones are weights, we represent this optimization
  // as a change in the storage bounds for the type for all constants of this
  // type.

        javaClassFile("compile/test/Person.class").exists()
        javaClassFile("compile/test/Person2.class").exists()
    }

    @Issue("https://github.com/gradle/gradle/issues/5750")
    def "include narrows down source files to compile"() {
        given:
        goodCode()

        and:
        file('src/main/java/Bar.java') << 'class Bar {}'
        buildFile << 'compileJava.include "**/Person*.java"'

// a default policy set to a PERMISSIVE.
// If there is at least one applicable config, returns should not be nil, and is a combined policy
// based on following rules:
// - It should have the setting from the most narrow scope (i.e workload-level is preferred over
// namespace-level, which is preferred over mesh-level).
// - When there are more than one policy in the same scope (i.e workload-level), the oldest one win.

             "or tf.relu6 to narrow the tensor range. Range: "
          << range << ", bit width: " << num_bits;
    }
    if (std::abs(max - min) < kNearZeroTolerance) {
      op.emitWarning() << "Tensor range (" << min << ", " << max
                       << ") is too narrow and it might cause overflow. "
                          "Expanding range symmetrically by "