add chain ip kube-proxy filter-output { type filter hook output priority -110 ; }
		add rule ip kube-proxy filter-output ct state new jump service-endpoints-check
		add rule ip kube-proxy filter-output ct state new jump firewall-check
		add chain ip kube-proxy filter-output-post-dnat { type filter hook output priority -90 ; }
		add rule ip kube-proxy filter-output-post-dnat ct state new jump cluster-ips-check

  return rewriter.create<arith::ConstantOp>(output.getLoc(), attr_type, attr);
}

Value ExpandedDynamicShape(PatternRewriter& rewriter, Value input,
                           DenseIntElementsAttr broadcast_dimensions,
                           Value output) {
  assert(mlir::cast<ShapedType>(output.getType()) &&
         "output type must be of ShapedType");

}

void CreateSubgraphTouchingRefVar(const Scope& s) {
  Output variable =
      ops::Variable(s.WithOpName("variable"), PartialTensorShape{}, DT_FLOAT);
  Output read = ops::Identity(s.WithOpName("read_ref_var"), variable);
  Output neg = ops::Negate(s.WithOpName("negate_ref"), read);
  Output add = ops::Add(s.WithOpName("add_ref"), neg, neg);

  Output constant =

            if (!s.ok()) {
              return;
            }
            node_map[n] = copy;
          }

          // Only handle input edges. Output edges will be added later as
          // its output nodes' input edges.
          for (auto e : n->in_edges()) {
            if (node_map.find(e->src()) == node_map.end()) {
              s = errors::Internal("Cannot find node image for ",

  %cst = "tfl.no_value"() {value = unit} : () -> none
  // expected-error @+1 {{expect output type has rank = 4, got output type tensor<64x84x32xf32>}}

  bool InferShapeForRestore(Operation* op);

  // Infers the shape IfOp outputs based on the shapes of the then and else
  // function result types.
  bool InferShapeForIf(IfOp op);

  // Infers the shape IfRegion outputs based on the shapes of the then and else
  // yields.
  bool InferShapeForIfRegion(IfRegionOp op);

  // Infers the shape CaseOp outputs based on the shapes of branch function
  // result types.

	kubeletUser = "kubelet"
)

// parseGetSubIdsOutput parses the output from the `getsubids` tool, which is used to query subordinate user or group ID ranges for
// a given user or group. getsubids produces a line for each mapping configured.
// Here we expect that there is a single mapping, and the same values are used for the subordinate user and group ID ranges.
// The output is something like:
// $ getsubids kubelet
// 0: kubelet 65536 2147483648

// ============================================================================
// The following functions tests example quantization patterns outputted from
// JAX Quantizer. JAX Quantizer should output integer types, which are
// composed into `UniformQuantized{|PerAxis}Type` via
// `compose_uniform_quantized_type_pass.cc`.
// ============================================================================

          "kind": "FlowSchema",
          "version": "v1beta3"
        }
      },
      "parameters": [
        {
          "description": "If 'true', then the output is pretty printed. Defaults to 'false' unless the user-agent indicates a browser or command-line HTTP tool (curl and wget).",
          "in": "query",
          "name": "pretty",
          "schema": {

          "kind": "FlowSchema",
          "version": "v1"
        }
      },
      "parameters": [
        {
          "description": "If 'true', then the output is pretty printed. Defaults to 'false' unless the user-agent indicates a browser or command-line HTTP tool (curl and wget).",
          "in": "query",
          "name": "pretty",
          "schema": {