func stack24()   { var buf [24]byte; use(buf[:]); C.callGoStackCheck() }
func stack28()   { var buf [28]byte; use(buf[:]); C.callGoStackCheck() }
func stack32()   { var buf [32]byte; use(buf[:]); C.callGoStackCheck() }
func stack36()   { var buf [36]byte; use(buf[:]); C.callGoStackCheck() }
func stack40()   { var buf [40]byte; use(buf[:]); C.callGoStackCheck() }
func stack44()   { var buf [44]byte; use(buf[:]); C.callGoStackCheck() }

func le_1_uint32(x uint32) bool          { return x <= 1 }
func gt_1_uint32(x uint32) bool          { return x > 1 }
func ge_1_uint32(x uint32) bool          { return x >= 1 }
func eq_1_uint32(x uint32) bool          { return x == 1 }
func ne_1_uint32(x uint32) bool          { return x != 1 }
func lt_126_uint32(x uint32) bool        { return x < 126 }
func le_126_uint32(x uint32) bool        { return x <= 126 }

  func.return %0 : tensor<8x16xf32>
// CHECK-LABEL: square
// CHECK:  "tfl.square"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16xf32>
}

func.func @neg(%arg0: tensor<8x16xf32>) -> tensor<8x16xf32> {
  %0 = "tf.Neg"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16xf32>
  func.return %0 : tensor<8x16xf32>
// CHECK-LABEL: neg
// CHECK:  "tfl.neg"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16xf32>
}

    func.return
  }
  func.func @empty_func() {
    func.return
  }
}

// -----

// Tests `tf_device.cluster_func` with bad `num_cores_per_replicas` attribute.

module attributes {tf.versions = {producer = 888 : i32}, tf.devices = ["/job:worker/replica:0/task:0/device:CPU:0", "/job:worker/replica:0/task:0/device:TPU_SYSTEM:0", "/job:worker/replica:0/task:0/device:TPU:0"]} {
  func.func @bad_num_cores_per_replica() {

	}
}

//go:noinline
func tu2copy_ssa(docopy bool, data [2]byte, x *[2]byte) {
	if docopy {
		*x = data
	}
}
func testUnalignedCopy2(t *testing.T) {
	var a [2]byte
	t2 := [2]byte{2, 3}
	tu2copy_ssa(true, t2, &a)
	want2 := [2]byte{2, 3}
	if a != want2 {
		t.Errorf("tu2copy got=%v, want %v\n", a, want2)
	}
}

//go:noinline
func tu3copy_ssa(docopy bool, data [3]byte, x *[3]byte) {

)

func init() {
	localSchemeBuilder.Register(RegisterConversions)
}

// RegisterConversions adds conversion functions to the given scheme.
// Public to allow building arbitrary schemes.
func RegisterConversions(s *runtime.Scheme) error {
	if err := s.AddGeneratedConversionFunc((*v1alpha2.AllocationResult)(nil), (*resource.AllocationResult)(nil), func(a, b interface{}, scope conversion.Scope) error {

  func.return %0 : tensor<4x2x!tf_type.string>
}

// -----

// CHECK-LABEL: func @testBitcast
func.func @testBitcast(%arg0: tensor<3x4xui16>) -> tensor<3x4x!tf_type.quint16> {
  %0 = "tf.Bitcast"(%arg0) : (tensor<3x4xui16>) -> tensor<3x4x!tf_type.quint16>
  func.return %0 : tensor<3x4x!tf_type.quint16>
}

// -----

// CHECK-LABEL: func @testBitcast_v2

    func.return %0 : tensor<*xi32>
  }
  func.func @partitioned_called_func(%arg0: tensor<?xi32>) -> (tensor<?xi32>) {
    func.return %arg0 : tensor<?xi32>
  }
  func.func @stateful_partitioned_call_func(%arg0: tensor<?xi32>) -> (tensor<?xi32>) {
    func.return %arg0 : tensor<?xi32>
  }
  func.func @tpu_partitioned_call_func(%arg0: tensor<?xi32>) -> (tensor<?xi32>) {

  func.return %0#0 : tensor<?xi32>
}

// -----

// CHECK-LABEL: testExp
func.func @testExp(tensor<? x f32>) -> tensor<? x f32> {
^bb0(%arg0: tensor<? x f32>):
  // CHECK: "tfl.exp"(%arg0)
  %0 = "tfl.exp"(%arg0): (tensor<? x f32>) -> tensor<? x f32>
  func.return %0 : tensor<? x f32>
}

// CHECK-LABEL: testFloor
func.func @testFloor(tensor<? x f32>) -> tensor<? x f32> {

// Name is an unqualified name.
type Name struct {
	Name string
}

func (n *Name) print(ps *printState) {
	ps.writeString(n.Name)
}

func (n *Name) Traverse(fn func(AST) bool) {
	fn(n)
}

func (n *Name) Copy(fn func(AST) AST, skip func(AST) bool) AST {
	if skip(n) {
		return nil
	}
	return fn(n)
}

func (n *Name) GoString() string {
	return n.goString(0, "Name: ")
}