pc=5049499 func=41 file=42 line=124
	pc=5048282 func=43 file=42 line=70
	pc=5021687 func=44 file=45 line=154
	pc=5057739 func=46 file=47 line=85
	pc=5057380 func=48 file=47 line=75
	pc=5057381 func=49 file=47 line=71
	pc=4965884 func=50 file=51 line=651
	pc=4964173 func=52 file=51 line=616
	pc=4961811 func=53 file=51 line=517
	pc=4960409 func=54 file=51 line=508
	pc=4958646 func=55 file=51 line=434

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() }

    llvm::StringRef name;
    mlir::func::FuncOp func;
  };
  llvm::SmallVector<NamedFunc, 8> named_funcs;
  llvm::SmallVector<mlir::func::FuncOp, 8> private_funcs;
  for (auto func : module.getOps<mlir::func::FuncOp>()) {
    auto exported_names = mlir::tf_saved_model::GetExportedNames(func);
    if (!exported_names.empty())
      named_funcs.push_back({exported_names.front(), func});
    else

// -----

module {
// CHECK-LABEL: func private @some_func
// CHECK-LABEL: func @func_with_call
func.func private @some_func(%arg0: tensor<100xf32>) -> tensor<100xf32> attributes {tf.api_implements = "lstm_b4e9f0e7-ac55-42bc-8ef2-8496419a608c"}
func.func @func_with_call(%arg0: tensor<100xf32>) -> tensor<100xf32> {
  %0 = func.call @some_func(%arg0) : (tensor<100xf32>) -> tensor<100xf32>
  func.return %0 : tensor<100xf32>
  }
}

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() {

)

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 (m *Subject) XXX_Merge(src proto.Message) {
	xxx_messageInfo_Subject.Merge(m, src)
}
func (m *Subject) XXX_Size() int {
	return m.Size()
}
func (m *Subject) XXX_DiscardUnknown() {
	xxx_messageInfo_Subject.DiscardUnknown(m)
}

var xxx_messageInfo_Subject proto.InternalMessageInfo

func (m *UserSubject) Reset()      { *m = UserSubject{} }
func (*UserSubject) ProtoMessage() {}

}
func (m *Subject) XXX_Merge(src proto.Message) {
	xxx_messageInfo_Subject.Merge(m, src)
}
func (m *Subject) XXX_Size() int {
	return m.Size()
}
func (m *Subject) XXX_DiscardUnknown() {
	xxx_messageInfo_Subject.DiscardUnknown(m)
}

var xxx_messageInfo_Subject proto.InternalMessageInfo

func (m *UserSubject) Reset()      { *m = UserSubject{} }
func (*UserSubject) ProtoMessage() {}