code: def test_data():
      """[Parallel | Learner] Test data"""
      idx = INDEXERS["subsemble"]()
      lyr = Layer("layer-scorer").push(make_group(idx, ECM, None))
      for lr in lyr.learners:
          lr.scorer = scorer
  
      run(lyr, "fit", X, y, return_preds=True)
      repr = lyr.data.__repr__()
      assert lyr.raw_data
      assert isinstance(lyr.raw_data, list)
      assert isinstance(lyr.data, dict)
      assert repr
      assert "score" in repr
  
file_path: mlens/mlens/parallel/tests/test_b4_layer_push_pop.py
imports: import os
  import numpy
  from mlens.index import INDEXERS
  from mlens.testing.dummy import Data, ECM
  from mlens.utils.dummy import Scale, LogisticRegression
  from mlens.parallel import make_group, Layer, run
  from mlens.externals.sklearn.base import clone
label_desc: Use image node_id 5 for calling a global function with example usage: test_data() without return types