code: def test_unwraps_mp_eigvals():
      """Test that a measurememnt process with autograd eigvals unwraps them to numpy."""
      import torch
  
      eigvals = torch.tensor([0.5, 0.5])
      m = qml.measurements.ExpectationMP(
          eigvals=eigvals, wires=qml.wires.Wires(0)
      )
  
      unwrapped_m = _convert_measurement_to_numpy_data(m)
      assert qml.math.get_interface(unwrapped_m.eigvals) == "numpy"
  
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 6 for calling a global function with example usage: test_unwraps_mp_eigvals() without return types