code: def run_before_and_after_tests():
      torch.set_default_dtype(torch.float64)
      yield
      torch.set_default_dtype(torch.float32)
  
imports: import numpy
  import pytest
  from param_shift_dev import ParamShiftDerivativesDevice
  import pennylane
  from pennylane.devices import DefaultQubit
  from pennylane.gradients import param_shift
  from pennylane import execute
  from pennylane.measurements import Shots
label_desc: Use image node_id 1 for calling a global function with example usage: run_before_and_after_tests() without return types