Defs map[*syntax.Name]Object

	// Uses maps identifiers to the objects they denote.
	//
	// For an embedded field, Uses returns the *TypeName it denotes.
	//
	// Invariant: Uses[id].Pos() != id.Pos()
	Uses map[*syntax.Name]Object

	// Implicits maps nodes to their implicitly declared objects, if any.
	// The following node and object types may appear:
	//

                   "defs argument",
                   i);
      return nullptr;
    }

    // Parse op def from character array.
    tensorflow::OpDef opdef;
    if (!tensorflow::protobuf::TextFormat::ParseFromString(tf_opdefs, &opdef)) {
      PyErr_Format(
          PyExc_ValueError,
          "Failed to parse opdefs at index %d of custom op defs argument: %s",
          i, tf_opdefs);

  LOCAL_OUTPUT_BUILD_CONTEXT="${LOCAL_OUTPUT_IMAGE_STAGING}/${KUBE_BUILD_IMAGE}"

  kube::version::get_version_vars
  kube::version::save_version_vars "${KUBE_ROOT}/.dockerized-kube-version-defs"

  # Without this, the user's umask can leak through.
  umask 0022
}

# ---------------------------------------------------------------------------
# Utility functions

)

cc_library(
    name = "tac-opt_lib",
    testonly = True,
    deps = [
        ":target_aware_conversion",
        "//tensorflow/compiler/mlir:tf_mlir_opt_main",
    ],
    alwayslink = 1,
)

# Binary with no hardwares linked.
tf_cc_binary(
    name = "tac-opt",
    testonly = True,
    deps = [
        ":tac-opt_lib",
    ],
)

# Binary with all backends linked.

    hdrs = [
        "tf_mlir_translate_cl.h",
    ],
    deps = [
        "@llvm-project//llvm:Support",
    ],
    alwayslink = 1,
)

cc_library(
    name = "export_graphdef",
    srcs = [
        "export_graphdef.cc",
    ],
    hdrs = [
        "export_graphdef.h",
    ],
    visibility = ["//visibility:public"],
    deps = [
        ":export_tf_dialect_op",

    ],
)

cc_library(
    name = "compile_mlir_util_no_tf_dialect_passes",
    srcs = ["compile_mlir_util.cc"],
    hdrs = ["compile_mlir_util.h"],
    visibility = ["//visibility:public"],
    deps = [
        "//tensorflow/compiler/mlir/quantization/stablehlo:bridge_passes",
        "//tensorflow/compiler/mlir/tensorflow",
        "//tensorflow/compiler/mlir/tensorflow:bridge_logger",

        "//learning/brain/mlir/bridge:__pkg__",
        "//tensorflow/compiler/mlir/quantization/stablehlo:__pkg__",
        "//tensorflow/compiler/mlir/tfrt/transforms/ifrt:__pkg__",
    ],
    deps = [
        ":device_type_proto_cc",
        "//tensorflow/compiler/jit:flags_headers",
        "//tensorflow/compiler/jit:shape_inference",
        "//tensorflow/compiler/mlir/tensorflow",

	ztunnelServer := &fakeZtunnel{}

	fakeIPSetDeps := ipset.FakeNLDeps()
	set := ipset.IPSet{V4Name: "foo-v4", Prefix: "foo", Deps: fakeIPSetDeps}
	netServer := newNetServer(ztunnelServer, podNsMap, iptablesConfigurator, NewPodNetnsProcFinder(fakeFs()), set)

	netServer.netnsRunner = func(fdable NetnsFd, toRun func() error) error {
		return toRun()
	}