* Simple implementation of memory based expiration.
     *
     * Use the maximum heap size of each daemon, not their actual memory usage.
     * Expire as much daemons as needed to free the requested memory under the threshold.
     */
    private class SimpleMemoryExpirationSelector implements Transformer<List<WorkerDaemonClient>, List<WorkerDaemonClient>> {

        private final long memoryBytesToRelease;
        private long releasedBytes;

		}
	}

	var m int
	if runtime.GOARCH == "amd64" {
		m = 1 // > 99% obtained on amd64, no backsliding
	} else if runtime.GOARCH == "riscv64" {
		m = 3 // XXX temporary update threshold to 97% for regabi
	} else {
		m = 2 // expect 98% elsewhere.
	}

	if len(nonStmtLines)*100 > m*len(lines) {

	// nondeterministic, so this test checks that we get the
	// desired outcome in a significant majority of cases.
	// The actual ratio of direct handoffs is much higher
	// (>90%) but we use a lower threshold to minimize the
	// chances that unrelated changes in the runtime will
	// cause the test to fail or become flaky.
	if ok < iter*2/3 {
		t.Fatal("direct handoff < 2/3:", ok, iter)
	}
}

var configLock sync.RWMutex

// Enabled - indicates if cache is enabled or not
func (c *Config) Enabled() bool {
	return c.Enable && c.Endpoint != ""
}

// MatchesSize verifies if input 'size' falls under cacheable threshold
func (c Config) MatchesSize(size int64) bool {
	configLock.RLock()
	defer configLock.RUnlock()

	return c.Enable && c.BlockSize > 0 && size <= c.BlockSize
}

// Update updates new cache frequency

			helperTable = slicing8TableISO
			// For smaller sizes creating extended table takes too much time
		} else if len(p) >= 2048 {
			// According to the tests between various x86 and arm CPUs, 2k is a reasonable
			// threshold for now. This may change in the future.
			helperTable = makeSlicingBy8Table(tab)
		} else {
			break
		}
		// Update using slicing-by-8
		for len(p) > 8 {
			crc ^= byteorder.LeUint64(p)

        call_op.emitRemark("Quantization is skipped for ")
            << call_op->getName().getStringRef().str() << " because it has "
            << current_num_elements
            << " elements which is fewer than the threshold("
            << min_num_elements_for_weights_ << " elements).";
        call_op->removeAttr(kQuantTraitAttrName);
      }
    }

    StringRef function_name =

  OpPassManager pass_manager;
  llvm::StringRef device_type = "XLA_CPU_JIT";
  absl::string_view kInlinePass =
      "inline{default-pipeline=canonicalize "
      "inlining-threshold=4294967295 max-iterations=4 }";

  CreateConvertMlirToXlaHloPipeline(pass_manager, device_type,
                                    /*enable_op_fallback=*/true,

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

// CHECK: tfrt.cost_threshold = 1024 : i64
module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 462 : i32}} {

// CHECK-LABEL: func @__forward_call_369
// CHECK-SAME: ([[in_chain:%.*]]: !tfrt.chain
// CHECK-SAME: [[arg1:%.*]]: !tfrt_fallback.tf_tensor {tf._user_specified_name = "inputs"},

			"Empty":        {},
			"Blank":        {""},
			"Double-Blank": {"", ""},
		},
		nil,
		"Blank: \r\nDouble-Blank: \r\nDouble-Blank: \r\n",
	},
	// Tests header sorting when over the insertion sort threshold side:
	{
		Header{
			"k1": {"1a", "1b"},
			"k2": {"2a", "2b"},
			"k3": {"3a", "3b"},
			"k4": {"4a", "4b"},
			"k5": {"5a", "5b"},
			"k6": {"6a", "6b"},
			"k7": {"7a", "7b"},
			"k8": {"8a", "8b"},

// <endcallsites>
// <endfuncpreamble>
func T_call_scoring_in_noninlinable_func(x int, sl []int) int {
	if x == 101 {
		// Drive up the cost of inlining this funcfunc over the
		// regular threshold.
		for i := 0; i < 10; i++ {
			for j := 0; j < i; j++ {
				sl = append(sl, append(sl, append(sl, append(sl, x)...)...)...)
				sl = append(sl, sl[0], sl[1], sl[2])
				x += calleeNoInline(x)
			}
		}
	}