// tf_executor.island {_parallel_execution_ids=r0:0,p0:1} wraps "tf.OpD"
// tf_executor.island {_parallel_execution_ids=r0:1} wraps "tf.OpB"
// tf_executor.island {_parallel_execution_ids=r0:1,p0:0} wraps "tf.OpC"
// tf_executor.island {_parallel_execution_ids=r0:1,p0:1} wraps "tf.OpD"
//
// "tf.OpA" will not have `_parallel_execution_ids` attr,

        %c = "tf.opC"(%b) : (tensor<i32>) -> tensor<f32>
        tf_device.return %c, %b : tensor<f32>, tensor<i32>
      }) {device = "CPU:0"} : () -> (tensor<f32>, tensor<i32>)
      %d = "tf.opD"() : () -> tensor<i1>
      tf_executor.yield %a, %launch#0, %launch#1, %d : tensor<i1>, tensor<f32>, tensor<i32>, tensor<i1>
    }
    tf_executor.fetch
  }
  func.return
}

// CHECK-NOT: tf_executor.island

// CHECK-SAME: ([[ARG_0:%.*]]: tensor<i32>)
// CHECK-NEXT: [[A:%.*]] = "tf.opA"([[ARG_0]])
// CHECK-NEXT: [[B:%.*]] = "tf.opB"([[A]])
// CHECK-NEXT: [[C:%.*]] = "tf.opC"([[A]])
// CHECK-NEXT: [[D:%.*]] = "tf.opD"([[C]])
// CHECK-NEXT: return [[B]], [[D]]
func.func @multiple_inner_ops(%arg0: tensor<i32>) -> (tensor<i32>, tensor<i32>) {
  %graph_result:2 = tf_executor.graph {
    %output0_0, %output0_1, %control0 = tf_executor.island {

        %2 = "tf.opA"() : () -> tensor<i1>
        %3 = "tf.opB"(%2) : (tensor<i1>) -> tensor<i1>
        tf_device.return %3 : tensor<i1>
      }, {
        %2 = "tf.opC"() : () -> tensor<i32>
        %3 = "tf.opD"(%2) : (tensor<i32>) -> tensor<i32>
        tf_device.return %3 : tensor<i32>
      }) : () -> (tensor<i1>, tensor<i32>)
      tf_executor.yield %1#0, %1#1 : tensor<i1>, tensor<i32>
    }

func.func @replicate_with_multiple_operands() {
  %0 = "tf.opA"() : () -> tensor<*xi1>
  %1 = "tf.opB"() : () -> tensor<*xi1>
  %2 = "tf.opC"() : () -> tensor<*xi1>
  %3 = "tf.opD"() : () -> tensor<*xi32>
  %4 = "tf.opE"() : () -> tensor<*xi32>
  %5 = "tf.opF"() : () -> tensor<*xi32>
  %6 = "tf.opG"() : () -> tensor<*xf32>
  %7 = "tf.opH"() : () -> tensor<*xf32>
  %8 = "tf.opI"() : () -> tensor<*xf32>

        %c = "tf.opC"(%b) : (tensor<i32>) -> tensor<f32>
        tf_device.return %c, %b : tensor<f32>, tensor<i32>
      }) {device = "CPU:0"} : () -> (tensor<f32>, tensor<i32>)
      %d = "tf.opD"() : () -> tensor<i1>
      tf_executor.yield %a, %launch#0, %launch#1, %d : tensor<i1>, tensor<f32>, tensor<i32>, tensor<i1>
    }
    tf_executor.fetch
  }
  func.return
}

// CHECK:      %[[A:.*]] = "tf.opA"