def METHOD_NAME(vector_size=40,
                           dense_width=128,
                           optimizer='rmsprop',
                           learn_rate_mult=1.0,
                           regularization=0.01,
                           verbose=1):
    """Return callable model.
    Returns
    -------
    callable:
        A function that return the Keras Sklearn model when
        called.
    """
    # check is tensorflow is available
    _check_tensorflow()
    model = Sequential()
    model.add(
        Dense(
            dense_width,
            input_dim=vector_size,
            kernel_regularizer=regularizers.l2(regularization),
            activity_regularizer=regularizers.l1(regularization),
            activation='relu',
        ))
    # add Dense layer with relu activation
    model.add(
        Dense(
            dense_width,
            kernel_regularizer=regularizers.l2(regularization),
            activity_regularizer=regularizers.l1(regularization),
            activation='relu',
        ))
    # add Dense layer
    model.add(Dense(1, activation='sigmoid'))
    optimizer_fn = _get_optimizer(optimizer, learn_rate_mult)
    # Compile model
    model.compile(
        loss='binary_crossentropy',
        optimizer=optimizer_fn,
        metrics=['acc'])
    if verbose >= 1:
        model.summary()
    return model