code: def test_custom_grid(self, transformX, transformY, transformA):
      # Creating a standard grid with the default parameters
      grid_size = 10
      grid_limit = 2.0
      grid_offset = 0.1
  
      disparity_moment = EqualizedOdds()
      X, y, A = _quick_data(False)
  
      disparity_moment.load_data(X, y, sensitive_features=A)
  
      grid = _GridGenerator(
          grid_size,
          grid_limit,
          disparity_moment.pos_basis,
          disparity_moment.neg_basis,
          disparity_moment.neg_basis_present,
          False,
          grid_offset,
      ).grid
  
      # Creating a custom grid by selecting only a few columns from the grid to try out
      indices = [7, 3, 4]
      grid = grid.iloc[:, indices]
  
      gs = GridSearch(
          estimator=LogisticRegression(solver="liblinear"),
          constraints=EqualizedOdds(),
          grid=grid,
      )
  
      # Check that fit runs successfully with the custom grid
      gs.fit(
          transformX(X), transformY(y), sensitive_features=transformA(A)
      )
  
      # Check that it trained the correct number of predictors
      assert len(gs.predictors_) == len(grid.columns)
  
imports: import logging
  from test.unit.fixes import get_sklearn_expected_1d_message
  from test.unit.input_convertors import conversions_for_1d, ensure_dataframe, ensure_ndarray
  from test.unit.reductions.conftest import is_invalid_transformation
  from test.unit.reductions.grid_search.utilities import _quick_data, assert_n_grid_search_results
  import numpy
  import pandas
  import pytest
  from sklearn.exceptions import NotFittedError
  from sklearn.linear_model import LinearRegression, LogisticRegression
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import StandardScaler
  from fairlearn.reductions import BoundedGroupLoss, DemographicParity, EqualizedOdds, GridSearch, ZeroOneLoss
  from fairlearn.reductions._grid_search._grid_generator import GRID_DIMENSION_WARN_TEMPLATE, GRID_DIMENSION_WARN_THRESHOLD, GRID_SIZE_WARN_TEMPLATE, _GridGenerator
  from fairlearn.utils._input_validation import _LABELS_NOT_0_1_ERROR_MESSAGE, _MESSAGE_Y_NONE
label_desc: Use image node_id 8 for calling the ArgumentTests obj's underlying member method code with example usage: obj.test_custom_grid(transformX, transformY, transformA) without return types