code: def test_la_binning(
      r, target, observed, exp_bin_edges, exp_bin_centers, expected_repr
  ):
      target_transf, _, rep_params = r(target, observed, None, [])
      bin_centers_hyb = rep_params[0].asnumpy()
      bin_edges_hyb = rep_params[1].asnumpy()
  
      assert np.allclose(
          exp_bin_edges.asnumpy(), bin_edges_hyb
      ), f"Bin edges mismatch. Expected: {exp_bin_edges} VS Actual: {bin_edges_hyb}."
      assert np.allclose(
          exp_bin_centers.asnumpy(), bin_centers_hyb
      ), f"Bin centers mismatch. Expected: {exp_bin_centers} VS Actual: {bin_centers_hyb}."
      assert np.allclose(
          expected_repr.asnumpy(), target_transf.asnumpy()
      ), f"Representation mismatch. Expected: {expected_repr} VS Actual: {target_transf}."
  
imports: import mxnet
  import numpy
  import pytest
  from gluonts.mx.representation import LocalAbsoluteBinning
label_desc: Use image node_id 1 for calling a global function with example usage: test_la_binning(r, target, observed, exp_bin_edges, exp_bin_centers, expected_repr) without return types