code: def calculate_grid(
      grid_limit, grid_size, disparity_moment, grid_offset=None
  ):
      X, y, A = _quick_data()
  
      disparity_moment.load_data(X, y, sensitive_features=A)
  
      return _GridGenerator(
          grid_size,
          grid_limit,
          disparity_moment.pos_basis,
          disparity_moment.neg_basis,
          disparity_moment.neg_basis_present,
          False,
          grid_offset,
      ).grid
  
file_path: fairlearn/test/unit/reductions/grid_search/test_grid_generator.py
imports: from test.unit.reductions.grid_search.utilities import _quick_data
  import numpy
  import pandas
  import pytest
  from fairlearn.reductions import DemographicParity, EqualizedOdds
  from fairlearn.reductions._grid_search.grid_search import _GridGenerator
  from fairlearn.reductions._moments.utility_parity import _ALL, _EVENT, _GROUP_ID, _SIGN
label_desc: Use image node_id 6 for calling a global function with example usage: calculate_grid(grid_limit, grid_size, disparity_moment, grid_offset) and returns: _GridGenerator