p.notifyHandlers()
		return nil
	}))
	p.webhooks = kclient.NewFiltered[*admissionregistrationv1.MutatingWebhookConfiguration](client, kubetypes.Filter{
		ObjectFilter: kubetypes.NewStaticObjectFilter(isTagWebhook),
	})
	p.index = kclient.CreateIndexWithDelegate[string, *admissionregistrationv1.MutatingWebhookConfiguration](p.webhooks,
		func(o *admissionregistrationv1.MutatingWebhookConfiguration) []string {
			rev := o.GetLabels()[label.IoIstioRev.Name]

func (p *Parser) checkAdvance(sec section) error {
	if p.section < sec {
		return ErrNotStarted
	}
	if p.section > sec {
		return ErrSectionDone
	}
	p.resHeaderValid = false
	if p.index == int(p.header.count(sec)) {
		p.index = 0
		p.section++
		return ErrSectionDone
	}
	return nil
}

func (p *Parser) resource(sec section) (Resource, error) {
	var r Resource
	var err error

		case ARNG_16B:
			c.checkindex(p, index, 15)
			Q = 1
			imm5 = 1
			imm5 |= index << 1
		case ARNG_2D:
			c.checkindex(p, index, 1)
			Q = 1
			imm5 = 8
			imm5 |= index << 4
		case ARNG_2S:
			c.checkindex(p, index, 3)
			Q = 0
			imm5 = 4
			imm5 |= index << 3
		case ARNG_4H:
			c.checkindex(p, index, 7)
			Q = 0
			imm5 = 2
			imm5 |= index << 2

			// cycle errors.
		}

		// reduce dependency count of all dependent nodes
		// and update priority queue
		for p := range n.pred {
			p.ndeps--
			heap.Fix(&pq, p.index)
		}

		// record the init order for variables with initializers only
		v, _ := n.obj.(*Var)
		info := check.objMap[v]
		if v == nil || !info.hasInitializer() {
			continue
		}

			// cycle errors.
		}

		// reduce dependency count of all dependent nodes
		// and update priority queue
		for p := range n.pred {
			p.ndeps--
			heap.Fix(&pq, p.index)
		}

		// record the init order for variables with initializers only
		v, _ := n.obj.(*Var)
		info := check.objMap[v]
		if v == nil || !info.hasInitializer() {
			continue
		}

  %4 = shape.shape_of %3 : tensor<?x28x28x16xf32> -> tensor<4xindex>
  %5 = stablehlo.dynamic_broadcast_in_dim %1, %4, dims = [3] : (tensor<16xf32>, tensor<4xindex>) -> tensor<?x28x28x16xf32>
  %6 = stablehlo.add %3, %5 : tensor<?x28x28x16xf32>
  %7 = shape.shape_of %6 : tensor<?x28x28x16xf32> -> tensor<4xindex>
  %8 = stablehlo.dynamic_broadcast_in_dim %2, %7, dims = [] : (tensor<f32>, tensor<4xindex>) -> tensor<?x28x28x16xf32>

  // CHECK: arith.divsi {{.*}} : index
  // CHECK: tensor.from_elements {{.*}} : tensor<3xindex>
  // CHECK: mhlo.real_dynamic_slice {{.*}} : (tensor<4x?x4xf32>, tensor<3xindex>, tensor<3xindex>, tensor<3xindex>) -> tensor<4x?x4xf32>
  // CHECK: muli {{.*}} : index
  // CHECK: muli {{.*}} : index
  // CHECK: tensor.from_elements {{.*}} : tensor<3xindex>
  // CHECK: tensor.from_elements {{.*}} : tensor<3xindex>

			t.Errorf("%v: expected no error, but got %v", tc.name, err)
		}
	}
}

type predictableNameGenerator struct {
	index int
}

func (p *predictableNameGenerator) GenerateName(base string) string {
	p.index++
	return fmt.Sprintf("%s%d", base, p.index)
}

func TestStoreCreateGenerateNameConflict(t *testing.T) {

  // CHECK-DAG: %[[VAR_SHAPE:.+]] = shape.shape_of %[[VARIANCE]] : tensor<?xf32> -> tensor<1xindex>
  // CHECK-DAG: %[[EPS_BCAST:.+]] =  "mhlo.dynamic_broadcast_in_dim"(%[[EPS]], %[[VAR_SHAPE]]) <{broadcast_dimensions = dense<> : tensor<0xi64>}> : (tensor<f32>, tensor<1xindex>) -> tensor<?xf32>
  // CHECK-DAG: %[[VARIANCE_EPS:.+]] = mhlo.add %[[VARIANCE]], %[[EPS_BCAST]] : tensor<?xf32>

  // NOT-CHECK-NEXT:   %[[RESULT_SHAPE:.+]] = shape.broadcast %[[LHS_SHAPE1]], %[[RHS_SHAPE]] : tensor<?xindex>, tensor<?xindex> -> tensor<?xindex>
  // NOT-CHECK-NEXT:   %[[RESULT_EXTENTS:.+]] = tensor.cast %[[RESULT_SHAPE]] : tensor<?xindex> to tensor<1xindex>
  // NOT-CHECK-DAG:    %[[LHS_BCAST:.+]] = "mhlo.dynamic_broadcast_in_dim"(%arg0, %[[RESULT_EXTENTS]]) <{broadcast_dimensions = dense<0> : tensor<1xi64>}>