"@babel/highlight": "^7.18.6"
      },
      "engines": {
        "node": ">=6.9.0"
      }
    },
    "node_modules/@babel/helper-validator-identifier": {
      "version": "7.19.1",
      "resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.19.1.tgz",
      "integrity": "sha512-awrNfaMtnHUr653GgGEs++LlAvW6w+DcPrOliSMXWCKo597CwL5Acf/wWdNkf/tfEQE3mjkeD1YOVZOUV/od1w==",

    status->status = InvalidArgument("Invalid GraphDef");
    return;
  }
  status->status = s->session->Extend(g);
}

}  // end extern "C"

// Reset helper for converting character arrays to string vectors.
static void TF_Reset_Helper(const TF_SessionOptions* opt,
                            const char** containers, int ncontainers,
                            TF_Status* status) {

}

func newGatewayProxy() *model.Proxy {
	return &model.Proxy{Type: model.Router, Metadata: &model.NodeMetadata{}}
}

// Helper function to extract TLS context from a cluster
func getTLSContext(t *testing.T, c *cluster.Cluster) *tls.UpstreamTlsContext {
	t.Helper()
	if c.TransportSocket == nil {
		return nil
	}
	tlsContext := &tls.UpstreamTlsContext{}

    return pool_params;
  }

  return std::nullopt;
}

namespace {

using ::mlir::tf_saved_model::kTfSavedModelExportedNamesAttr;
using ::mlir::tf_saved_model::kTfSavedModelIndexPathAttr;

// Helper struct that wraps inputs/outputs of a single SignatureDef.
struct SignatureDefData {
  // Note, we are using maps here to make order deterministic
  // for easily testing only.

	Leaf  string
	Graph []trustGraphEdge
}

func genCertEdge(t *testing.T, subject string, key crypto.Signer, mutateTmpl func(*Certificate), certType int, issuer *Certificate, signer crypto.Signer) *Certificate {
	t.Helper()

	serial, err := rand.Int(rand.Reader, big.NewInt(100))
	if err != nil {
		t.Fatalf("failed to generate test serial: %s", err)
	}
	tmpl := &Certificate{
		SerialNumber: serial,

      return rewriter.notifyMatchFailure(
          conv_op,
          "Unsupported detphwise transpose convolution with non-1 channel "
          "multiplier");
    }

    // Slicing with dynamic offsets (helper method advised)
    auto create_slice = [&](mlir::Value tensor, int depth_idx, int channel_idx,
                            bool is_kernel = false) -> mlir::Value {
      std::vector<int64_t> tensor_shape =

	for i := range scores {
		scores[i].Score = inj.NormalizeRes
	}
	return nil
}

func collectAndComparePluginMetrics(t *testing.T, wantExtensionPoint, wantPlugin string, wantStatus framework.Code) {
	t.Helper()
	m := metrics.PluginExecutionDuration.WithLabelValues(wantPlugin, wantExtensionPoint, wantStatus.String())

	count, err := testutil.GetHistogramMetricCount(m)
	if err != nil {

  if (req.IsValid()) return values(req);

  return nullptr;
}

// Context used during ShapeInference. This class contains common information
// that is required by the individual shape inference helper functions (e.g.,
// TF Graph version, constant values computed, etc.)
class ShapeInference {
 public:
  ShapeInference(int64_t graph_version, ModuleOp module,
                 bool propagate_caller_callee_constants,

                                           int new_dims) {
  std::vector<int64_t> new_shape(new_dims, 1);
  std::copy_backward(old_shape.begin(), old_shape.end(), new_shape.end());
  return new_shape;
}

// Helper method that given and 'current_index' representing
// index in broadcasted tensor, get the index in the flat original tensor.
// 'shape' is the original shape with padding to match result shape.

getScroll(element, 'left');\n  const modifier = subtract ? -1 : 1;\n  rect.top += scrollTop * modifier;\n  rect.bottom += scrollTop * modifier;\n  rect.left += scrollLeft * modifier;\n  rect.right += scrollLeft * modifier;\n  return rect;\n}\n","/*\n * Helper to detect borders of a given element\n * @method\n * @memberof Popper.Utils\n * @param {CSSStyleDeclaration} styles\n * Result of `getStyleComputedProperty` on the given element\n * @param {String} axis - `x` or `y`\n * @return {number} borders -...