{"tf.Yield"(%if3) : (!tf_variant) -> ()})
        {is_stateless = true} : (tensor<i1>) -> !tf_variant
    %if5 = "tf.IfRegion"(%arg0) ({"tf.Yield"(%if4) : (!tf_variant) -> ()},
                                 {"tf.Yield"(%if4) : (!tf_variant) -> ()})
        {is_stateless = true} : (tensor<i1>) -> !tf_variant
    %if6 = "tf.IfRegion"(%arg0) ({"tf.Yield"(%if5) : (!tf_variant) -> ()},

            // expected-remark@above {{ID: 2}}
              tf_executor.yield %arg1 : tensor<i1>
              // expected-remark@above {{ID: 1}}
            }
            tf_executor.fetch %island#0 : tensor<i1>
            // expected-remark@above {{ID: 3}}
          }
          "tf.Yield"(%graph) : (tensor<i1>) -> ()
          // expected-remark@above {{ID: 5}}
        }, { // Else region

//      tf_device.return
//    }) {} : () -> (tensor<i1>)
//    tf_executor.yield %4 : tensor<i1>
//  }
//  tf_executor.fetch %3#0 : tensor<i1>
//
// gets lowered to:
//
//  %0 = tf_executor.island {
//    tf_executor.yield
//  }
//  %1:2 = tf_executor.island {
//    %2 = "tf.opA"(%arg0) : (tensor<i1>) -> tensor<i1>
//    tf_executor.yield %2 : tensor<i1>
//  }
//

      // CHECK: tf.Yield
      "tf.Yield"(%recv) : (tensor<f32>) -> ()
    }, {
      // CHECK-NOT: _xla_token_input_nodes
      %add = "tf.Add"(%arg1, %arg1) : (tensor<f32>, tensor<f32>) -> tensor<f32>

      // CHECK: tf.Yield
      "tf.Yield"(%add) : (tensor<f32>) -> ()
    }) { is_stateless = true}: (tensor<i1>) -> tensor<f32>

    %2 = "tf.IfRegion"(%arg0) ({
      %3 = "tf.StringToNumber"(%arg1) {out_type = f32} : (tensor<!tf_type.string>) -> tensor<f32>
      "tf.Yield"(%3) : (tensor<f32>) -> ()
     },  {
      %4 = "tf.Const"() {value = dense<1.0> : tensor<f32>} : () -> tensor<f32>
      "tf.Yield"(%4) : (tensor<f32>) -> ()
    }) {is_stateless = true} : (tensor<i1>) -> (tensor<f32>)
    %5 = "tf.Identity"(%2) : (tensor<f32>) -> tensor<f32>

  func.func @main() {
    tf_executor.graph {
      %control = tf_executor.island {
        tf_executor.yield
      }
      tf_executor.fetch %control : !tf_executor.control
    }
    tf_executor.graph {
      %control = tf_executor.island {
        tf_executor.yield
      }
      tf_executor.fetch %control : !tf_executor.control
    }
    return
  }

    "tfl.yield"(%1) : (tensor<i1>) -> ()
  },  {
  ^bb0(%arg0: tensor<*xi32>, %arg1: tensor<*xf32>):
    // CHECK: call @WhileOp_body
    // CHECK-SAME: (tensor<*xi32>, tensor<*xf32>, tensor<i32>)
    %1:3 = func.call @WhileOp_body(%arg0, %arg1, %cst) : (tensor<*xi32>, tensor<*xf32>, tensor<i32>) -> (tensor<*xi32>, tensor<*xf32>, tensor<i32>)
    "tfl.yield"(%1#0, %1#1) : (tensor<*xi32>, tensor<*xf32>) -> ()

  func.func @main() {
    tf_executor.graph {
      %control = tf_executor.island {
        tf_executor.yield
      }
      tf_executor.fetch %control : !tf_executor.control
    }
    tf_executor.graph {
      %control = tf_executor.island {
        tf_executor.yield
      }
      tf_executor.fetch %control : !tf_executor.control
    }
    return
  }

    // CHECK: "tf.ReadVariableOp"([[name]])
    %cond = builtin.unrealized_conversion_cast to tensor<i1>
    %0 = "tf.IfRegion"(%cond) ({
      "tf.Yield"(%arg0) : (tensor<!tf_type.resource<tensor<10xf32>>>) -> ()
    }, {
      "tf.Yield"(%arg0) : (tensor<!tf_type.resource<tensor<10xf32>>>) -> ()
    }) { is_stateless = false} : (tensor<i1>) -> tensor<!tf_type.resource<tensor<10xf32>>>

  auto it = block.rbegin();
  YieldOp yield = dyn_cast<YieldOp>(*it++);

  if (it == block.rend()) return std::nullopt;

  // Operation which is expected to consume all the call results.
  Operation* call_consumer = yield;

  // Allow a single ToBoolOp between the call and the yield (valid only
  // when the yield has a single operand)
  if (allow_to_bool && yield.getNumOperands() == 1 && isa<ToBoolOp>(*it)) {