code: def test_normalize_1d_classification_binary():
      """Tests 1d classification normalization."""
      y = np.array([0, 0, 1, 0, 1, 1, 0])
      expected = np.array(
          [
              [[1.0, 0.0]],
              [[1.0, 0.0]],
              [[0.0, 1.0]],
              [[1.0, 0.0]],
              [[0.0, 1.0]],
              [[0.0, 1.0]],
              [[1.0, 0.0]],
          ]
      )
      y_out = normalize_prediction_shape(
          y, mode="classification", n_tasks=1, n_classes=2
      )
      assert y_out.shape == (7, 1, 2)
      assert np.array_equal(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 8 for calling a global function with example usage: test_normalize_1d_classification_binary() without return types