343cb214a384df7061e0e4300bc376ae4f66b5ef,deepchem/models/tests/test_overfit.py,TestOverfit,test_residual_lstm_singletask_classification_overfit,#TestOverfit#,725

Before Change

        dc.metrics.accuracy_score)

    with g.as_default():
      support_model = dc.nn.SequentialSupportGraph(n_feat)
      
      // Add layers
      // output will be (n_atoms, 64)
      support_model.add(dc.nn.GraphConv(64, activation="relu"))
      // Need to add batch-norm separately to test/support due to differing
      // shapes.
      // output will be (n_atoms, 64)
      support_model.add_test(dc.nn.BatchNormalization(epsilon=1e-5, mode=1))
      // output will be (n_atoms, 64)
      support_model.add_support(dc.nn.BatchNormalization(epsilon=1e-5, mode=1))
      support_model.add(dc.nn.GraphPool())
      support_model.add_test(dc.nn.GraphGather(test_batch_size))
      support_model.add_support(dc.nn.GraphGather(support_batch_size))

      // Apply a residual lstm layer
      support_model.join(dc.nn.ResiLSTMEmbedding(
          test_batch_size, support_batch_size, max_depth))

      with self.test_session() as sess:
        model = dc.models.SupportGraphClassifier(
          sess, support_model, test_batch_size=test_batch_size,

After Change

    classification_metric = dc.metrics.Metric(dc.metrics.accuracy_score)

    support_model = dc.nn.SequentialSupportGraph(n_feat)

    // Add layers
    // output will be (n_atoms, 64)
    support_model.add(dc.nn.GraphConv(64, n_feat, activation="relu"))
    // Need to add batch-norm separately to test/support due to differing
    // shapes.
    // output will be (n_atoms, 64)
    support_model.add_test(dc.nn.BatchNormalization(epsilon=1e-5, mode=1))
    // output will be (n_atoms, 64)
    support_model.add_support(dc.nn.BatchNormalization(epsilon=1e-5, mode=1))
    support_model.add(dc.nn.GraphPool())
    support_model.add_test(dc.nn.GraphGather(test_batch_size))
    support_model.add_support(dc.nn.GraphGather(support_batch_size))

    // Apply a residual lstm layer
    support_model.join(
        dc.nn.ResiLSTMEmbedding(test_batch_size, support_batch_size, 64,
                                max_depth))

    model = dc.models.SupportGraphClassifier(
        support_model,
        test_batch_size=test_batch_size,

Instances