code: def test_rolling_var_uniform_window():
      """
      Pandas adopts an online variance calculation algorithm. This gives a
      floating point artifact.
  
      In cudf, each window is computed independently from the previous window,
      this gives better numeric precision.
      """
  
      s = pd.Series([1e8, 5, 5, 5])
      expected = s.rolling(3).var()
      got = cudf.from_pandas(s).rolling(3).var()
  
      assert_eq(expected, got)
  
imports: import math
  from contextlib import contextmanager
  import numpy
  import pandas
  import pytest
  import cudf
  from cudf.core._compat import PANDAS_GE_150
  from cudf.testing._utils import _create_pandas_series_float64_default, assert_eq
  from cudf.testing.dataset_generator import rand_dataframe
label_desc: Use image node_id 6 for calling a global function with example usage: test_rolling_var_uniform_window() without return types