foo480()
	foo481()
	foo482()
	foo483()
	foo484()
	foo485()
	foo486()
	foo487()
	foo488()
	foo489()
	foo490()
	foo491()
	foo492()
	foo493()
	foo494()
	foo495()
	foo496()
	foo497()
	foo498()
	foo499()
	foo500()
	foo501()
	foo502()
	foo503()
	foo504()
	foo505()
	foo506()
	foo507()
	foo508()
	foo509()
	foo510()
	foo511()
}

  function {
    signature {
      name: "foo5"
    }
  }
  function {
    signature {
      name: "foo6"
    }
  }
  function {
    signature {
      name: "foo7"
    }
  }
  function {
    signature {
      name: "foo8"
    }
  }
  function {
    signature {
      name: "foo9"
    }
  }
  function {
    signature {
      name: "foo10"
    }
  }
  function {

	c.Set("foo4", "bar")
	c.Set("foo5", "bar")
	c.Set("foo6", "bar")
	c.Set("foo7", "bar")

	wg := new(sync.WaitGroup)
	workers := runtime.NumCPU()
	each := b.N / workers
	wg.Add(workers)

	b.ResetTimer()
	for i := 0; i < workers; i++ {
		go func() {
			for j := 0; j < each; j++ {
				c.Get("foo1")
				c.Get("foo2")
				c.Get("foo3")
				c.Get("foo5")
				c.Get("foo6")
				c.Get("foo7")

    }

    def "old build script classloaders are collected"() {
        given:
        buildFile << """
            class Foo0 {
                static final byte[] MEMORY_HOG = new byte[10 * 1024 * 1024]
            }
            task myTask() {
                doLast {
                    println new Foo0()
                }
            }
        """

        expect:
        for(int i = 0; i < 35; i++) {

# CHECK-LABEL:  func @main() {
# CHECK:    "tf.LegacyCall"() <{_disable_call_shape_inference = true, f = @foo0}> {device = ""}
# CHECK:    "tf.LegacyCall"() <{_disable_call_shape_inference = false, f = @bar0}> {device = ""}

# CHECK-LABEL:  func private @foo0()
# CHECK: "tf.LegacyCall"() <{_disable_call_shape_inference = false, f = @bar0}> {device = ""}

# the names are matching between the function definition and the uses / call
# site (a numerical suffix may be appended).

# CHECK: "tf.LegacyCall"(%outputs) <{_disable_call_shape_inference = false, f = @foo0}> {device = ""}

// crash 7
type foo7 interface { bar() }
type x7[A any] struct{ foo7 }
func main7() { var _ foo7 = x7[int]{} }

// crash 8
type foo8[A any] interface { ~A /* ERROR "cannot be a type parameter" */ }
func bar8[A foo8[A]](a A) {}

// crash 9
type foo9[A any] interface { foo9 /* ERROR "invalid recursive type" */ [A] }
func _() { var _ = new(foo9[int]) }

// crash 12

# In GraphDef custom gradient functions are modeled using GradientDef which
# links the function and its gradient. In MLIR a TF ops gradient function is
# added to its list of function attributes.

# CHECK: func private @foo0(
# CHECK:   tf.gradient = @foo_grad

node {
  name: "Const"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "value"
    value {

    )

    static final UBER_MOBILE_APP = new IncrementalAndroidTestProject(
        templateName: 'uberMobileApp',
        pathToChange: 'leafModuleAvg/src/main/java/leafModuleAvgpackageJava0/Foo0.java',
        taskToRunForChange: ':rootModule:assembleDebug'
    )

    String pathToChange
    String taskToRunForChange

    @Override
    void configure(CrossVersionPerformanceTestRunner runner) {

		return "" // ERROR "not enough return values\n\thave \(string\)\n\twant \(string, int\)|not enough arguments to return"
	default:
		return "lizard", 10
	}
}

type S int
type T string
type U float64

func foo5() (S, T, U) {
	if false {
		return "" // ERROR "not enough return values\n\thave \(string\)\n\twant \(S, T, U\)|not enough arguments to return"
	} else {
		ptr := new(T)