code: def test_bin_mapper_identity_repeated_values(
      max_bins, n_distinct, multiplier
  ):
      data = np.array(list(range(n_distinct)) * multiplier).reshape(
          -1, 1
      )
      # max_bins is the number of bins for non-missing values
      n_bins = max_bins + 1
      binned = _BinMapper(n_bins=n_bins).fit_transform(data)
      assert_array_equal(data, binned)
  
imports: import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_equal
  from sklearn.ensemble._hist_gradient_boosting.binning import _BinMapper, _find_binning_thresholds, _map_to_bins
  from sklearn.ensemble._hist_gradient_boosting.common import ALMOST_INF, X_BINNED_DTYPE, X_DTYPE
  from sklearn.utils._openmp_helpers import _openmp_effective_n_threads
label_desc: Use image node_id 10 for calling a global function with example usage: test_bin_mapper_identity_repeated_values(max_bins, n_distinct, multiplier) without return types