if (!reached_compile_threshold) {
    VLOG(2) << "Not compiling cluster " << function.name()
            << " because it has not reached compile threshold; threshold is "
            << *compile_threshold << " execution count "
            << current_request_count << ".";
  }
  return reached_compile_threshold;
}

// RUN: tf-tfrt-opt -tf-executor-to-tfrt-pipeline="enable-optimizer=true tfrt-cost-threshold=1024" %s | FileCheck %s --dump-input=fail

// Check that unused While op results and the associated ops are removed.

module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 462 : i32}} {
  func.func @while_cond_lt9(%arg0: tensor<i32>, %arg1: tensor<i32>) -> tensor<i1> {

    $('.card').each(function (index, row) {
        var currentTags = $(row).attr('tag');
        if (currentTags === undefined) {
            currentTags = ''
        }
        // tag="FAILURE-THRESHOLD(4.16%),FLAKY(9.30%)"
        // tag="UNTAGGED"
        currentTags = currentTags.split(',').map(tag => tag.split('(')[0])
        if (selectedTags.some(tag => currentTags.indexOf(tag) != -1)) {
            $(row).show()

    }

    @Test
    public void test_TmpFileHasBeenDeletedAfterResponseWasClosed() throws Exception {
        // ## Arrange ##
        CurlRequest req = new MockCurlRequest(Curl.Method.POST, "http://dummy");
        req.threshold(0); // always create tmp file

        // ## Act ##
        long before = countTmpFiles();
        logger.info("Before request. Number of temp files: " + before);
        req.execute(res -> {

          - --cpu={{ base_metrics_server_cpu }}
          - --extra-cpu=0.5m
          - --memory={{ base_metrics_server_memory }}
          - --extra-memory={{ metrics_server_memory_per_node }}Mi
          - --threshold=5
          - --deployment=metrics-server-v0.7.1
          - --container=metrics-server
          - --poll-period=30000
          - --estimator=exponential

	{"-fno-split-stack"},
	{"-fstack-xxx"},
	{"-fno-stack-xxx"},
	{"-fsanitize=hands"},
	{"-g"},
	{"-ggdb"},
	{"-march=souza"},
	{"-mcmodel=medium"},
	{"-mcpu=123"},
	{"-mfpu=123"},
	{"-mlarge-data-threshold=16"},
	{"-mtune=happybirthday"},
	{"-mstack-overflow"},
	{"-mno-stack-overflow"},
	{"-mmacosx-version"},
	{"-mnop-fun-dllimport"},
	{"-pthread"},
	{"-std=c99"},
	{"-xc"},
	{"-D", "FOO"},

// input sizes, such as tf.Shape and tf.Reshape, are whitelisted to have cheap
// cost. This cost analysis is expected to be used conservatively (eg. use a low
// threshold to decide whether a cost is cheap or expensive), as it might not be
// accurate in some cases.
//
class CostAnalysis {
 public:
  explicit CostAnalysis(
      mlir::func::FuncOp func_op,

     */
    public int getThreshold() {
        return 0;
    }

    /**
     * <b>Warning</b>: ignored.
     */
    public void setThreshold(int threshold) {}

    /**
     * <b>Warning</b>: ignored (always return <code>null</code>).
     */
    public Logger getChildLogger(String name) {
        return null;
    }

    public String getName() {

// RUN: tf-tfrt-opt -pass-pipeline='builtin.module(func.func(tf-tensor-device-copy),tfrt-lower-tf-savedmodel{hoist-invariant-ops=true},tf-to-tfrt{tfrt-cost-threshold=1024 tfrt-merge-inter-dependent-streams=true})' %s | FileCheck %s --dump-input-filter=all

// CHECK-NOT: tf_saved_model.semantics
// CHECK: tfrt.cost_threshold = 1024
// CHECK-SAME: tfrt.merge_inter_dependent_streams = true
module attributes {tf_saved_model.semantics} {

// logging is based on Verbosity levels, where 0 is the most important. We treat
// levels 0-3 as info level and 4+ as debug; there are no warnings. This
// threshold is fairly arbitrary based on inspection of Kubernetes usage and
// https://kubernetes.io/docs/reference/kubectl/cheatsheet/#kubectl-output-verbosity-and-debugging.
// Errors are passed through as errors.