// CHECK: {{.*tf.While.*body = @while_body.* cond = @while_cond.* parallel_iterations = 3}}
    %0 = "tf.While"(%cst) {body = @while_body, cond = @while_cond, is_stateless = false, parallel_iterations = 3} : (tensor<i32>) -> (tensor<i32>)
    return
  }
  func.func private @while_body(%arg0: tensor<i32>) -> (tensor<i32>) {
    // metadata ops

    %0 = "tf.While"(%cst_main) {body = @while_body, cond = @while_cond, is_stateless = false} : (tensor<i32>) -> (tensor<i32>)
    // expected-error @+1 {{'tf.While' op multiple users of function.}}
    %1 = "tf.While"(%cst_main) {body = @while_body, cond = @while_cond, is_stateless = false} : (tensor<i32>) -> (tensor<i32>)
    return
  }
  func.func private @while_body(%arg0: tensor<i32>) -> (tensor<i32>) {

  func.return
}
// CHECK: func @while_body(%[[BARG0:.*]]: tensor<f32>)
func.func @while_body(%arg0: tensor<*x!tf_type.resource<tensor<f32>>>, %arg1: tensor<*x!tf_type.resource<tensor<f32>>>)
    -> (tensor<*x!tf_type.resource<tensor<f32>>>, tensor<*x!tf_type.resource<tensor<f32>>>) {
  // CHECK: %[[WHILE:.*]] = "tf.While"(%[[BARG0]])
  %0:2 = "tf.While"(%arg0, %arg1) {

  func.return %1 : tensor<i1>
}

// The @while_body function is a Multi-hosts function which contains three
// parts:
//   - A local subgraph which contains both local ops and remote_run kernels to
//     trigger remote subgraphs
//   - Two remote subgraph which contains remote ops on worker:1 and worker:2.
// CHECK: func @while_body(%[[ARG_0:.*]]: tensor<i32> {tf.device = "/job:localhost/replica:0/task:0/device:CPU:0"})

    %cst = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
    %cst_0 = "tf.Const"() {value = dense<1.0> : tensor<1x5x5x1024xf32>} : () -> tensor<1x5x5x1024xf32>
    // Check that these constants are remained in constants.
    // CHECK: func private @while_body

// CHECK-NEXT:    %0 = "tf.Less"(%arg0, %arg1) : (tensor<i32>, tensor<i32>) -> tensor<i1>
// CHECK-NEXT:    return %0 : tensor<i1>

// CHECK-LABEL: func.func private @"map/while_body"

  return %r : tensor<i1>
}

// CHECK-LABEL: func @while_body_if
func.func @while_body_if(%cond: tensor<i1>, %x: tensor<i1>, %y: tensor<i1>, %z: tensor<i32>) -> (tensor<i1>, tensor<i1>, tensor<i1>, tensor<i32>) {

// CHECK: func private @while_body
// CHECK-LABEL: testWhileRegionTrivialCasts
func.func private @while_cond(%arg0 : tensor<4xf32>, %arg1 : tensor<i32>) -> tensor<i1>
func.func private @while_body(%arg0 : tensor<4xf32>, %arg1 : tensor<i32>) -> (tensor<4xf32>, tensor<i32>)
func.func @testWhileRegionTrivialCasts(%arg0 : tensor<*xf32>, %arg1 : tensor<i32>) -> tensor<*xf32> {
  // CHECK: [[Result:%.*]]:2 = "tf.While"(%arg0, %arg1) <{body = @while_body, cond = @while_cond

  %0 = "tf.Const"() {value = dense<9> : tensor<i32>} : () -> tensor<i32>
  %1 = "tf.Less"(%arg0, %0) {} : (tensor<i32>, tensor<i32>) -> tensor<i1>
  func.return %1 : tensor<i1>
}

func.func @while_body(%arg0: tensor<i32>) -> tensor<i32> {
  %1 = "tf.AddV2"(%arg0, %arg0) {} : (tensor<i32>, tensor<i32>) -> tensor<i32>
  func.return %1 : tensor<i32>
}

  AppendFunctionArguments(while_body, num_chains, chaining_data_type);
  AppendFunctionResults(while_body, num_chains, chaining_data_type);

  // Insert identity ops with control dep
  ChainResourceOps(while_body, chain_resource_to_ops_map,
                   resource_equivalence_classes, ops_connected_to_fetch,
                   num_old_outputs);
  // Modify all the while ops referencing the body function and the