cb4ea667b426ebc6595cc0e8be81c94955266c9c,deepchem/utils/test/test_generator_evaluator.py,TestGeneratorEvaluator,test_compute_model_performance_multitask_classifier,#TestGeneratorEvaluator#,17

Before Change

    dataset = NumpyDataset(X, y)

    features = Feature(shape=(None, n_features))
    label = Label(shape=(None, n_tasks, n_classes))
    dense = Dense(out_channels=n_tasks * n_classes, in_layers=[features])
    logits = Reshape(shape=(None, n_tasks, n_classes), in_layers=dense)
    output = SoftMax(in_layers=[logits])
    smce = SoftMaxCrossEntropy(in_layers=[label, logits])

After Change

    features = layers.Input(shape=(n_data_points // 2, n_features))
    dense = layers.Dense(n_tasks * n_classes)(features)
    logits = layers.Reshape((n_tasks, n_classes))(dense)
    output = layers.Softmax()(logits)
    keras_model = tf.keras.Model(inputs=features, outputs=[output, logits])
    model = dc.models.KerasModel(
        keras_model,
        dc.models.losses.SoftmaxCrossEntropy(),

Instances