// RUN: tf-mlir-translate -mlir-to-graphdef %s -o - | FileCheck %s

func.func @main() {
  tf_executor.graph {
    %outputs, %control = tf_executor.island wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_INT32", name = "Constant", value = dense<0> : tensor<i32>} : () -> tensor<i32>
    %outputs_0, %control_1 = tf_executor.island wraps "tf.LegacyCall"(%outputs) {_tpu_replicate = "cluster", device = "", f = @foo0} : (tensor<i32>) -> tensor<i32>
    tf_executor.fetch
  }

// CHECK-NEXT:         }
// CHECK-NEXT:       }
// CHECK:          }
// CHECK-NEXT:   }
func.func @bar() {
  tf_executor.graph {
    %0:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", name = "tf.Const", value = dense<1> : tensor<i32>} : () -> tensor<i32>
    %1:2 = tf_executor.island wraps "tf.Empty"(%0#0) {dtype = "tfdtype$DT_FLOAT", name = "tf.Empty"} : (tensor<i32>) -> tensor<*xf32>
    tf_executor.fetch

  attributes  {tf.entry_function = {inputs = "args_0,args_1", outputs = "rets_0,rets_1"}} {
    %0:2 = tf_executor.graph {
      %1:3 = tf_executor.island wraps "tf.IdentityN"(%arg0, %arg1) {T = ["tfdtype$DT_FLOAT", "tfdtype$DT_INT32"], device = "", name = "identity"} : (tensor<*xf32>, tensor<2x4x6x8xi32>) -> (tensor<*xf32>, tensor<2x4x6x8xi32>)
      tf_executor.fetch %1#0, %1#1 : tensor<*xf32>, tensor<2x4x6x8xi32>
    }

// CHECK-NEXT:         tensor_shape {
// CHECK-NEXT:         }
// CHECK-NEXT:       }
// CHECK-NEXT:     }
// CHECK-NEXT:   }
// CHECK:      }
    %0:2 = tf_executor.island wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_INT32", value = dense<0> : tensor<i32>} : () -> tensor<i32> loc("predicate")

// CHECK:      node {
// CHECK-NEXT:   name: "Case"
// CHECK-NEXT:   op: "Case"
// CHECK-NEXT:   input: "predicate"
// CHECK:        attr {