Add functional layer tools

[crowsonkb]

Adds two functional tools for working with layers, sequence and repeat. They are simple composable functions that allow you to write cleaner code when using the Functional API. Instead of ugly code like:

input_layer = Input(shape=(16,))
x = Dense(8, activation='relu')(input_layer)
x = Dense(8, activation='relu')(x)
x = Dense(8, activation='relu')(x)
x = Dense(1)(x)
model = Model(input_layer, x)

applying the current layer to the previous layer manually on each line, sequence allows you to write:

input_layer = Input(shape=(16,))
output = sequence(
    Dense(8, activation='relu'),
    Dense(8, activation='relu'),
    Dense(8, activation='relu'),
    Dense(1),
)(input_layer)
model = Model(input_layer, output)

sequence takes any number of callables mapping a tensor to a tensor and returns a callable mapping a tensor to a tensor. So you can logically nest sequence calls, as in this example:

def residual_block(units):
    return lambda a: sequence(
        Activation('relu'),
        Dense(units),
        Activation('relu'),
        Dense(units),
        lambda b: Add()([a, b]),
    )(a)

output = sequence(
    residual_block(16),
    residual_block(16),
    Dense(1),
)(input_layer)

repeat, which takes a repeat count and a layer factory function, can be used to simplify creation of a deep model, as follows:

output = sequence(
    repeat(4, lambda: residual_block(16)),
    Dense(8),
    repeat(4, lambda: residual_block(8)),
    Dense(1),
)(input_layer)

As you can see, these functions allow you to easily create deep models without repetitive code.