b8fe52f9320760236c097153c40708d8994a31c0,tutorials/mnist_blackbox.py,,substitute_model,#Any#Any#Any#,76

Before Change

    // Define a fully connected model (it"s different than the black-box)
    layers = [Flatten(input_shape=input_shape),
              Dense(200),
              Activation("relu"),
              Dropout(0.5),
              Dense(200),
              Activation("relu"),

After Change

              ReLU(),
              Dropout(0.5),
              Linear(200),
              ReLU(),
              Dropout(0.5),
              Linear(nb_classes),
              Softmax()]

    return MLP(layers, input_shape)


def train_sub(sess, x, y, bbox_preds, X_sub, Y_sub, nb_classes,
              nb_epochs_s, batch_size, learning_rate, data_aug, lmbda):

Instances