// CHECK-LABEL: bias_add
func.func @bias_add(%arg0: tensor<1x10x10x32xf32>, %arg1: tensor<32xf32>) -> tensor<1x10x10x32xf32> {
  %0 = "tf.BiasAdd"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", data_format = "NHWC"} : (tensor<1x10x10x32xf32>, tensor<32xf32>) -> tensor<1x10x10x32xf32>
  func.return %0 : tensor<1x10x10x32xf32>

// CHECK-SAME: (%[[ARG0:.*]]: tensor<i1>, %[[ARG1:.*]]: tensor<4xf32>)
func.func @test_supported_lowering_of_tf_if_region2(%arg0: tensor<i1>, %arg1: tensor<4xf32>) -> () {
  "tf.IfRegion"(%arg0) ({
    func.call @test_if_then2(%arg1) : (tensor<4xf32>) -> ()
    "tf.Yield"() : () -> ()
  },  {
    func.call @test_if_else2(%arg1) : (tensor<4xf32>) -> ()
    "tf.Yield"() : () -> ()

public class AllowedMethodTypesClass {
    public void validMethod(String arg1, String arg2) {

    }

    public File invalidReturnType(String arg1, String arg2) {
        return null;
    }

    public void invalidParameterType(String arg1, File arg2) {

    }

    public <T extends File> void invalidTypeParameterBoundType(String arg1, String arg2) {

    }

// CHECK-LABEL: func @fold_identity_n_test
func.func @fold_identity_n_test(%arg0: tensor<2x2xf32>, %arg1: tensor<2x2xf32>) -> (tensor<2x2xf32>, tensor<2x2xf32>) {
  // CHECK: tf.MatMul
  %outputs = "tf.MatMul"(%arg0, %arg1) {device = "TPU", transpose_a = false, transpose_b = false} : (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>

func libfuzzerTraceCmp1(arg0, arg1 uint8, fakePC uint)  {}
func libfuzzerTraceCmp2(arg0, arg1 uint16, fakePC uint) {}
func libfuzzerTraceCmp4(arg0, arg1 uint32, fakePC uint) {}
func libfuzzerTraceCmp8(arg0, arg1 uint64, fakePC uint) {}

func libfuzzerTraceConstCmp1(arg0, arg1 uint8, fakePC uint)  {}
func libfuzzerTraceConstCmp2(arg0, arg1 uint16, fakePC uint) {}

func.func @main(%arg0: tensor<4x10x15xf32>, %arg1: tensor<4x15x17xf32>) -> tensor<4x10x17xf32> {
  %0 = "tfl.batch_matmul"(%arg0, %arg1) {adj_x = false, adj_y = false} : (tensor<4x10x15xf32>, tensor<4x15x17xf32>) -> tensor<4x10x17xf32>
  func.return %0:  tensor<4x10x17xf32>

// CHECK-LABEL: main

	fakePC = fakePC % retSledSize
	libfuzzerCallTraceIntCmp(&__sanitizer_cov_trace_cmp4, uintptr(arg0), uintptr(arg1), uintptr(fakePC))
}

//go:nosplit
func libfuzzerTraceCmp8(arg0, arg1 uint64, fakePC uint) {
	fakePC = fakePC % retSledSize
	libfuzzerCallTraceIntCmp(&__sanitizer_cov_trace_cmp8, uintptr(arg0), uintptr(arg1), uintptr(fakePC))
}

//go:nosplit

// CHECK-LABEL: func @device_func_3
// CHECK-NOT: tf.aliasing_output
func.func @device_func_3(%arg0: tensor<f32>, %arg1: tensor<f32>) -> (tensor<f32>, tensor<f32>) {
  func.return %arg1, %arg0 : tensor<f32>, tensor<f32>
}

// CHECK-LABEL: func @skip_multiple_reads_of_resource
func.func @skip_multiple_reads_of_resource(%arg0: !tf_res_f32, %arg1: !tf_res_f32) {
  %0 = "tf.ReadVariableOp"(%arg0) : (!tf_res_f32) -> tensor<f32>

  func.return %1 : tensor<1xf32>
}

func.func @cond_true(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>) -> tensor<*xf32> {
  %0 = tfl.add %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<*xf32>
  func.return %0 : tensor<*xf32>
}

func.func @cond_false(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>) -> tensor<*xf32> {
  %0 = tfl.mul %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<*xf32>
  func.return %0 : tensor<*xf32>

// CHECK-LABEL: module
module {
  // CHECK-LABEL: func @main
  // CHECK-SAME:    %[[ARG0:.*]]: tensor<10xi32>, %[[ARG1:.*]]: tensor<10xi32>
  func.func @main(%arg0: tensor<10xi32>, %arg1: tensor<10xi32>) -> tensor<10xi32> {
    // CHECK:      %[[RESULT:.*]] = "tf.XlaCallModule"(%[[ARG0]], %[[ARG1]])
    // CHECK-SAME:   Sout = [#tf_type.shape<?>]
    // CHECK-NOT:    function_list
    // CHECK-SAME:   module = ""