code: def _assert_predictions_equal(converted, expected):
      for k, v in expected.items():
          if isinstance(v, (int, float)):
              assert converted[k] - v <= (0.01 + v * 0.01)
          elif isinstance(v, (list, tuple)):
              if len(v) == 1 or isinstance(v[0], str):
                  assert converted[k] == v
              else:
                  np.testing.assert_allclose(
                      converted[k], v, atol=0.01, rtol=0.01
                  )
          else:
              assert converted[k] == v
  
imports: import os
  import random
  import numpy
  import pytest
  import fiftyone
  import fiftyone.zoo
  import fiftyone.utils.labelstudio
  import fiftyone.core.labels
label_desc: Use image node_id 13 for calling a global function with example usage: _assert_predictions_equal(converted, expected) without return types