bf1337afb8d75f0bbd8725c14830b8798bceb33e,autokeras/net_transformer.py,,transform,#Any#,40

Before Change

def transform(model):
    models = []

    for index, layer in enumerate(model.layers):
        if isinstance(layer, Dense):
            models.append(to_deeper_dense_model(model, layer))
            models.append(to_wider_dense_model(model, layer))
        elif is_conv_layer(layer):
            models.append(to_deeper_conv_model(model, layer))
            models.append(to_wider_conv_model(model, layer))

    models.append(to_skip_connection_model(model))

    return models

After Change

def transform(model):
    models = []
    for i in range(constant.N_NEIGHBORS):
        operation = randint(0, 2)

        if operation == 0:
            // wider
            models.append(to_wider_model(model))

Instances