if err := uninstallWasmExtension(t, pluginName, path); err != nil {
			t.Fatal(err)
		}
		sendTraffic(t, check.ResponseHeader(injectedHeader, ""), retry.Converge(2))
	})
}

func applyWasmConfig(ctx framework.TestContext, ns string, args map[string]any, path string) error {
	return ctx.ConfigIstio().EvalFile(ns, args, path).Apply()
}

# missing package, only to remove that package when resolving its dependencies.
#
# If we naively iterate 'go mod tidy' until the dependency graph converges, this
# scenario may fail to converge.

# The import graph used in this test looks like:
#
# m --- x
#       |
#       x_test --- y
#
# The module dependency graph of m is initially empty.
# Modules x and y look like:
#

               DeferActivationTransposeForMaxOp>(&ctx);
  if (failed(applyPatternsAndFoldGreedily(func_op, std::move(patterns)))) {
    func_op->emitWarning() << "Failed to converge patterns: " << getArgument();
  }
}

         "datasource": {
            "type": "datasource",
            "uid": "-- Mixed --"
         },
         "description": "Count of active and pending proxies managed by each instance.\nPending is expected to converge to zero.\n",
         "gridPos": {
            "h": 10,
            "w": 8,
            "x": 8,
            "y": 14
         },
         "id": 13,
         "interval": "1m",
         "options": {

	// Calling GoroutineProfile twice in a row should find the same number of goroutines,
	// but it's possible there are goroutines just about to exit, so we might end up
	// with fewer in the second call. Try a few times; it should converge once those
	// zombies are gone.
	for i := 0; ; i++ {
		n1, ok := GoroutineProfile(nil) // should fail, there's at least 1 goroutine
		if n1 < 1 || ok {

							util.PromDiff(t, prom, c, destinationQuery)
							return err
						}
						// This query will continue to increase due to readiness probe; don't wait for it to converge
						if _, err := prom.QuerySum(c, appQuery); err != nil {
							util.PromDiff(t, prom, c, appQuery)
							return err
						}

                                              target_opset_);
    patterns.add<QuantizeAvgPoolOpPattern>(ctx);
  }
  if (failed(applyPatternsAndFoldGreedily(func, std::move(patterns)))) {
    func.emitWarning("Failed to converge pattern at QuantizePass.");
  }

  if (!shouldKeepUnusedQdqPattern()) {
    RewritePatternSet patterns_2(&getContext());
    patterns_2.add<RemoveUnusedQdqPattern>(ctx);

		sort.Strings(expected)
		if !reflect.DeepEqual(got[cluster], expected) {
			return fmt.Errorf("wanted %v got %v. All endpoints: %+v", expected, got[cluster], got)
		}
		return nil
	}, retry.Converge(2), retry.Timeout(time.Second*2), retry.Delay(time.Millisecond*10))
}

func expectServiceEndpointsFromIndex(t *testing.T, ei *model.EndpointIndex, svc *model.Service, port int, expected []EndpointResponse) {
	t.Helper()

  // is not the same as the result index, which means there is "crosstalk"
  // between 2 or more operands. In that case, we do an iterative propagation
  // of resource IDs till the results converge.
  bool change = true;
  while (change) {
    change = false;
    for (auto result : filter_resources(while_op->getResults())) {
      if (IsUnknownResource(result)) continue;

  // Ophint python converter converted tf node pattern.
  patterns.add<LegalizeUnidirectionalSequenceLstm,
               LegalizeUnidirectionalSequenceRnn>(context);
}

bool applyPatterns(func::FuncOp func, ConversionTarget& target,
                   FrozenRewritePatternSet& frozenPatterns) {
  // Keep trying to convert.