func.func @add_v2_uint32(%arg0: tensor<ui32>, %arg1: tensor<ui32>) -> tensor<ui32> {
  %0 = "tf.AddV2"(%arg0, %arg1) : (tensor<ui32>, tensor<ui32>) -> tensor<ui32>
  func.return %0 : tensor<ui32>

  // CHECK-LABEL: add_v2_uint32
  // CHECK:  %[[CAST:.*]] = "tf.Cast"(%arg0) <{Truncate = false}> : (tensor<ui32>) -> tensor<i32>
  // CHECK:  %[[CAST1:.*]] = "tf.Cast"(%arg1) <{Truncate = false}> : (tensor<ui32>) -> tensor<i32>

  TF_DerivedResultTypeAttr dtype = TF_DerivedResultTypeAttr<0>;
}

// TODO(lyandy): Investigate supported dtypes (`minval`, `maxval`, `output`) for
// `tf.StatefulUniformInt`. tf2xla kernels support i32, i64, ui32, and ui64
// while TensorFlow CPU/GPU kernels only support i32 and i64.
def TF_StatefulUniformIntOp : TF_Op<"StatefulUniformInt", []> {
  let summary = "Outputs random integers from a uniform distribution.";