Definition of the LeNet-like embedder

lenet_like_embedder.py

def get_lenet_like_embedder(
    input_shape,
    act='elu', l2_reg=1e-3, filter_sz=5, num_filters=24, num_dense_neurons=512,
):
    """
    Returns a 2-tuple of (input, embedding_layer) that can later be used
    to create a model that builds on top of the embedding_layer.
    """
    inp = Input(input_shape)
    
    x = Conv2D(num_filters, (filter_sz, filter_sz),
               padding='same', kernel_regularizer=l2(l2_reg),
               activation=act)(inp)
    x = MaxPooling2D(2, 2)(x)

    x = Conv2D(2*num_filters, (filter_sz, filter_sz),
               padding='same', kernel_regularizer=l2(l2_reg),
               activation=act)(x)
    x = MaxPooling2D(2, 2)(x)

    x = Conv2D(4*num_filters, (filter_sz, filter_sz),
               padding='same', kernel_regularizer=l2(l2_reg),
               activation=act)(x)
    x = MaxPooling2D(2, 2)(x)

    x = Dropout(.5)(x)
    x = Flatten()(x)

    x = Dense(num_dense_neurons, kernel_regularizer=l2(l2_reg), activation=act)(x)
    x = Dropout(.5)(x)
    x = Dense(num_dense_neurons//2, kernel_regularizer=l2(l2_reg), activation=act)(x)
    emb = Dropout(.5)(x)

    return inp, emb