)

cc_library(
    name = "error_collector",
    srcs = ["error_collector.cc"],
    hdrs = ["error_collector.h"],
    deps = [
        ":types_util",
        "//tensorflow/lite/python/metrics:converter_error_data_proto_cc",
        "@com_google_absl//absl/strings",
    ],
)

cc_library(
    name = "error_collector_inst",
    srcs = ["error_collector_inst.cc"],
    hdrs = ["error_collector_inst.h"],

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    default_visibility = ["//visibility:public"],
    licenses = ["notice"],
)

cc_library(
    name = "freeze_saved_model",
    srcs = ["freeze_saved_model.cc"],
    hdrs = ["freeze_saved_model.h"],
    deps = [
        "//tensorflow/cc/saved_model:loader",
        "//tensorflow/core:core_cpu",
        "//tensorflow/core:lib",

	if d == 0 {
		d = defaultTCPKeepAliveIdle
	} else if d < 0 {
		return nil
	}

	// The kernel expects seconds so round to next highest second.
	secs := int(roundDurationUp(d, time.Second))
	err := fd.pfd.SetsockoptInt(syscall.IPPROTO_TCP, syscall.TCP_KEEPALIVE, secs)
	runtime.KeepAlive(fd)
	return wrapSyscallError("setsockopt", err)
}

func setKeepAliveInterval(fd *netFD, d time.Duration) error {
	if d == 0 {

load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],
)

filegroup(
    name = "headers",
    srcs = [
        "stream_executor.h",
    ],
    visibility = ["//tensorflow:__subpackages__"],
)

cc_library(
    name = "stream_executor_hdrs",
    hdrs = ["stream_executor.h"],

    ],
)

pytype_strict_library(
    name = "stablehlo",
    srcs = ["stablehlo.py"],
    srcs_version = "PY3",
    visibility = ["//visibility:public"],
    deps = [
        ":stablehlo_extension",
    ],
)

py_strict_test(
    name = "stablehlo_test",
    srcs = ["stablehlo_test.py"],
    python_version = "PY3",
    deps = [
        ":stablehlo",

	s.addService(t, "svc1",
		map[string]string{},
		map[string]string{},
		[]int32{80}, map[string]string{"app": "a"}, "10.0.0.1")
	s.assertEvent(t, s.podXdsName("pod1"), s.svcXdsName("svc1"))

	s.labelService(t, "svc1", testNS, map[string]string{constants.AmbientUseWaypointLabel: "test-wp"})
	s.assertEvent(t, s.svcXdsName("svc1"))
	s.assertNoEvent(t)

        ":friends",
    ],
)

package_group(
    name = "friends",
    packages = [
        "//tensorflow/compiler/mlir/lite/...",
    ],
)

tf_cc_binary(
    name = "odml-converter",
    srcs = ["odml_converter_main.cc"],
    compatible_with = get_compatible_with_portable(),
    visibility = [
        "//tensorflow/compiler/mlir/lite/stablehlo/odml_converter:__subpackages__",

        "//tensorflow/compiler/tf2xla:__pkg__",
        "//tensorflow/dtensor/mlir:__pkg__",
    ],
    licenses = ["notice"],
)

cc_library(
    name = "lower_cluster_to_runtime_ops",
    srcs = ["lower_cluster_to_runtime_ops.cc"],
    hdrs = [
        "lower_cluster_to_runtime_ops.h",
    ],
    deps = [
        ":runtime_passes",
        "//tensorflow/compiler/jit:flags_headers",

    ],
)

tf_proto_library(
    name = "device_type_proto",
    srcs = ["device_type.proto"],
    cc_api_version = 2,
    visibility = [
        "//learning/serving/contrib/tfrt/mlir/saved_model_analysis:__pkg__",
    ],
)

cc_library(
    name = "cluster_tf",
    srcs = ["cluster_tf.cc"],
    hdrs = ["cluster_tf.h"],
    visibility = [

    default_visibility = [
        "//tensorflow/compiler/mlir/lite/experimental/tac:__subpackages__",
    ],
    licenses = ["notice"],
)

cc_library(
    name = "tac_wrapper_lib",
    srcs = ["tac_wrapper.cc"],
    hdrs = [
        "tac_wrapper.h",
    ],
    deps = [
        "//tensorflow/compiler/mlir/lite/experimental/tac:common",