code: def test_preserves_trainable_params():
      """Test that convert_to_numpy_parameters preserves the trainable parameters property."""
      ops = [
          qml.RX(qml.numpy.array(2.0), 0),
          qml.RY(qml.numpy.array(3.0), 0),
      ]
      qs = qml.tape.QuantumScript(ops)
      qs.trainable_params = {0}
      output = convert_to_numpy_parameters(qs)
      assert output.trainable_params == [0]
  
file_path: pennylane/tests/transforms/test_convert_to_numpy_parameters.py
imports: import pytest
  import numpy
  import pennylane
  from pennylane.transforms import convert_to_numpy_parameters
  from pennylane.transforms.convert_to_numpy_parameters import _convert_op_to_numpy_data, _convert_measurement_to_numpy_data
label_desc: Use image node_id 2 for calling a global function with example usage: test_preserves_trainable_params() without return types