auto loc = cluster_func.getLoc();
    auto new_cluster_func = builder.create<tf_device::ClusterFuncOp>(
        loc, cluster_func.getResultTypes(), operands, cluster_func->getAttrs());
    cluster_func.replaceAllUsesWith(new_cluster_func);
    func::FuncOp func = cluster_func.getFuncOp();
    Block& block = func.front();
    for (Value read_operand : read_operands)

			// doesn't automatically preclude some scenarios from happening.
			t.Parallel()

			if ignoreWatchCacheTests && tt.ignoreForWatchCache {
				t.Skip()
			}

			if tt.pred.GetAttrs == nil {
				tt.pred.GetAttrs = getAttrs
			}

			out := &example.PodList{}
			storageOpts := storage.ListOptions{
				ResourceVersion:      tt.rv,
				ResourceVersionMatch: tt.rvMatch,
				Predicate:            tt.pred,

    input_matchers_ = std::move(inputs);
  }

  void set_control_deps(NodeSeqMatcher control_deps) {
    DCHECK(IsEmpty());
    control_deps_ = std::move(control_deps);
  }

  void set_attr(AttrKeyValuePair attr) {
    DCHECK(IsEmpty());
    attr_ = std::move(attr);
  }

  bool IsEmpty() const {
    return !name().has_value() && !op().has_value() && !inputs().has_value() &&

    }
    OpBuilder builder(call);
    auto new_call = builder.create<CallOp>(
        call.getLoc(), info.decomposed_callee.getFunctionType().getResults(),
        new_operands, call->getAttrs());
    new_call->setAttr(
        "f", SymbolRefAttr::get(
                 builder.getContext(),
                 const_cast<func::FuncOp&>(info.decomposed_callee).getName()));
    for (int64_t i = 0; i < call.getNumResults(); ++i) {

}

func componentStatusPredicate(options *metainternalversion.ListOptions) storage.SelectionPredicate {
	pred := storage.SelectionPredicate{
		Label:    labels.Everything(),
		Field:    fields.Everything(),
		GetAttrs: nil,
	}
	if options != nil {
		if options.LabelSelector != nil {
			pred.Label = options.LabelSelector
		}
		if options.FieldSelector != nil {
			pred.Field = options.FieldSelector
		}
	}

    state.addAttributes(batch_norm->getAttrs());
    Operation *op = rewriter.create(state);
    rewriter.replaceOp(batch_norm, op->getResults());

    // Depending on the case, we may fuse the add, the relu, or both.
    if (!add_op || add_op.getZ().hasOneUse()) {
      // We fuse the Relu only if the add has a single use, otherwise we only
      // fuse the add itself.
      op->setAttr("activation_mode", rewriter.getStringAttr("Relu"));

		TableConvertor: printerstorage.TableConvertor{TableGenerator: printers.NewTableGenerator().With(printersinternal.AddHandlers)},
	}
	options := &generic.StoreOptions{RESTOptions: optsGetter, AttrFunc: persistentvolumeclaim.GetAttrs}
	if err := store.CompleteWithOptions(options); err != nil {
		return nil, nil, err
	}

	statusStore := *store
	statusStore.UpdateStrategy = persistentvolumeclaim.StatusStrategy

    op->setAttr("f", SymbolRefAttr::get(rewriter.getContext(),
                                        new_float_func.getName()));

    return success();
  }

  LogicalResult matchAndRewrite(TF::PartitionedCallOp op,
                                PatternRewriter& rewriter) const override {
    const auto f_attr = mlir::dyn_cast<FlatSymbolRefAttr>(op.getFAttr());
    // Non-quantizable op

		TableConvertor: printerstorage.TableConvertor{TableGenerator: printers.NewTableGenerator().With(printersinternal.AddHandlers)},
	}
	options := &generic.StoreOptions{RESTOptions: optsGetter, AttrFunc: job.GetAttrs}
	if err := store.CompleteWithOptions(options); err != nil {
		return nil, nil, err
	}

	statusStore := *store
	statusStore.UpdateStrategy = job.StatusStrategy
	statusStore.ResetFieldsStrategy = job.StatusStrategy

      return true;
    }
  }

  SymbolTable symbol_table(op->getParentOfType<ModuleOp>());
  // Check the functions associated to CaseOp, IfOp and WhileOp.
  for (const NamedAttribute& attr : op->getAttrs()) {
    FlatSymbolRefAttr symbol_attr =
        dyn_cast_or_null<FlatSymbolRefAttr>(attr.getValue());
    if (!symbol_attr) continue;

    func::FuncOp target_func = dyn_cast_or_null<func::FuncOp>(