// CHECK-NEXT: [[CONST:%.*]] = "tf.Const"
  %0 = "tf.Const"() {value = dense<1.000000e+00> : tensor<f32>} : () -> tensor<f32>

  // CHECK-NEXT: "tf.AssignSubVariableOp"([[UNUSED_RESOURCE]], [[CONST]])

  // CHECK:      "tf_device.cluster"
  // CHECK-NEXT:   "tf.ReadVariableOp"([[USED_RESOURCE]])
  // CHECK-NEXT:   "tf.NoOp"
  // CHECK-NEXT:   tf_device.return

    tf_device.return
  }) : () -> ()
  func.return
}


// Tests that composite tf.AssignSubVariableOp operation is decomposed using
// SubOp.

// CHECK-LABEL: func @decompose_assign_sub_variable_op
func.func @decompose_assign_sub_variable_op() -> () {
  "tf_device.cluster"() ({

    const Cluster& cluster) {
  Node* n = GetOnlyNodeIn(cluster);
  if (!n) {
    return false;
  }

  if (n->type_string() != "AssignAddVariableOp" &&
      n->type_string() != "AssignSubVariableOp") {
    return false;
  }

  DataType dtype;
  if (!TryGetNodeAttr(n->def(), "dtype", &dtype) || !DataTypeIsInteger(dtype)) {
    return false;
  }

  Node* const_input = nullptr;