%4 = "tf.ReadVariableOp"(%0) {dtype = i32} : (tensor<*x!tf_type.resource<tensor<*xi32>>>) -> tensor<1xi32>
    tf_device.return %4 : tensor<1xi32>
  }) {cluster_attr = "cluster_attr"} : () -> tensor<1xi32>

  // CHECK: return %[[CLUSTER_RES]]#0
  func.return %1 : tensor<1xi32>
}

// -----

// Tests that anonymous internal resource operations are eliminated.

```mlir
  %2 = "tf.A"(%arg0) : (tensor<?xi32>) -> tensor<?xi32>
  %3 = "tf.B"(%2) {device = "tpu0"} : (tensor<?xi32>) -> tensor<?xi32>
  %4 = "tf.C"(%2, %3) {device = "tpu0"} : (tensor<?xi32>, tensor<?xi32>) -> tensor<?xi32>
  %5 = "tf.D"(%4) : (tensor<?xi32>) -> tensor<?xi32>
```

After the pass, we will have:

```mlir
  %0 = "tf.A"(%arg0) : (tensor<?xi32>) -> tensor<?xi32>
  %1 = "tf_device.launch"() ( {