code: def test_validate_adjoint_trainable_params_obs_warning():
      """Tests warning raised for validate_adjoint_trainable_params with trainable observables."""
      tape = qml.tape.QuantumScript([], [qml.expval(2 * qml.PauliX(0))])
      with pytest.warns(
          UserWarning,
          match="Differentiating with respect to the input ",
      ):
          validate_adjoint_trainable_params(tape)
  
imports: import pytest
  import pennylane
  from pennylane.operation import Operation
  from pennylane.tape import QuantumScript
  from pennylane import DeviceError
  from pennylane.devices.preprocess import no_sampling, validate_device_wires, validate_multiprocessing_workers, validate_adjoint_trainable_params, _operator_decomposition_gen, decompose, validate_observables, validate_measurements
label_desc: Use image node_id 2 for calling a global function with example usage: test_validate_adjoint_trainable_params_obs_warning() without return types