code: def test_normalize_2d_classification_binary():
      """Tests 2d classification normalization."""
      # Of shape (N, n_classes)
      y = np.random.randint(2, size=(10, 1))
      y_expected = np.expand_dims(
          dc.metrics.to_one_hot(np.squeeze(y)), 1
      )
      y_out = normalize_prediction_shape(
          y, mode="classification", n_tasks=1, n_classes=2
      )
      assert y_out.shape == (10, 1, 2)
      assert np.array_equal(y_expected, y_out)
  
imports: import numpy
  import deepchem
  from deepchem.metrics import to_one_hot
  from deepchem.metrics import from_one_hot
  from deepchem.metrics import threshold_predictions
  from deepchem.metrics import handle_classification_mode
  from deepchem.metrics import normalize_prediction_shape
  from deepchem.metrics import normalize_weight_shape
label_desc: Use image node_id 11 for calling a global function with example usage: test_normalize_2d_classification_binary() without return types