return
}

// -----

func.func @init(%arg0: tensor<4xf32>) -> tensor<7xf32> {
  %0 = builtin.unrealized_conversion_cast to tensor<7xf32>
  return %0 : tensor<7xf32>
}

def BatchFunctionOp : FallbackAsync_Op<"batch_function",
    [Pure, CoreRT_TypedAttributeTrait]> {
  let summary = "Fallback ExecuteOp specialized for tf.BatchFunction.";
  let description = [{
    This kernel executes a variant tf.BatchFunction kernel that supports having
    the `f` attribute as a BEF function.

    Example:
      %res = tfrt_fallback_async.batch_function device("/CPU:0") @f(%input, %captured_input)  {

2FB8          ; mapped                 ; 9996          # 3.0  KANGXI RADICAL HEAD
2FB9          ; mapped                 ; 9999          # 3.0  KANGXI RADICAL FRAGRANT
2FBA          ; mapped                 ; 99AC          # 3.0  KANGXI RADICAL HORSE
2FBB          ; mapped                 ; 9AA8          # 3.0  KANGXI RADICAL BONE

    * If this permission is still desired, run the following command to explicitly grant it, either before or after upgrading to 1.7:
    *     kubectl create clusterrolebinding kube-system-default --serviceaccount=kube-system:default --clusterrole=cluster-admin

// CHECK-LABEL: func @testTensorListElementShape
func.func @testTensorListElementShape(%arg0: tensor<!tf_type.variant<tensor<2x4xf32>>>) -> tensor<2xi32> {
  %0 = "tf.TensorListElementShape"(%arg0) : (tensor<!tf_type.variant<tensor<2x4xf32>>>) -> tensor<2xi32>
  // CHECK:         [[cst:%.*]] = "tf.Const{{.*}} dense<{{\[}}2, 4]> : tensor<2xi32>
  // CHECK-NEXT:    return [[cst]] : tensor<2xi32>

        "composite" tensors, such as `tf.RaggedTensor`, as inputs.
    *   Fix device placement issues related to datasets with ragged tensors of
        strings (i.e. variant encoded data with types not supported on GPU).
    *   'experimental_follow_type_hints' for tf.function has been deprecated.
        Please use input_signature or reduce_retracing to minimize retracing.