code: def test_groupby_quantile_all_na_group_masked_interp(
      interpolation, any_numeric_ea_dtype
  ):
      # GH#37493
      df = DataFrame(
          {"a": [1, 1, 1, 2], "b": [1, 2, 3, pd.NA]},
          dtype=any_numeric_ea_dtype,
      )
      result = df.groupby("a").quantile(
          q=[0.5, 0.75], interpolation=interpolation
      )
  
      if any_numeric_ea_dtype == "Float32":
          expected_dtype = any_numeric_ea_dtype
      else:
          expected_dtype = "Float64"
  
      expected = DataFrame(
          {"b": [2.0, 2.5, pd.NA, pd.NA]},
          dtype=expected_dtype,
          index=pd.MultiIndex.from_arrays(
              [
                  pd.Series([1, 1, 2, 2], dtype=any_numeric_ea_dtype),
                  [0.5, 0.75, 0.5, 0.75],
              ],
              names=["a", None],
          ),
      )
      tm.assert_frame_equal(result, expected)
  
imports: import numpy
  import pytest
  import pandas
  from pandas import DataFrame, Index
  import pandas._testing
label_desc: Use image node_id 16 for calling a global function with example usage: test_groupby_quantile_all_na_group_masked_interp(interpolation, any_numeric_ea_dtype) without return types