MTDzi

def get_lenet_like_model(
        input_shape, num_outputs,
        l2_reg=1e-3, filter_sz=5, num_filters=24, num_dense_neurons=512,
):
	inp = Input(input_shape)
	x = Conv2D(num_filters, (filter_sz, filter_sz),
             	   padding='same', kernel_regularizer=l2(l2_reg))(inp)
	x = MaxPooling2D(2, 2)(x)
	x = ELU()(x)

MTDzi

def clip_throttle(throttle, curr_speed, target_speed):
    return np.clip(
        throttle - 0.1 * (curr_speed-target_speed),
        0.25,
        1.0
    )

MTDzi

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)
    

MTDzi

def add_throttle_upon_steer_w_odometry(
    outputs_spec, embed_getter,
    act='elu', l2_reg=1e-3, num_dense_neurons=512,
):
    """Build output layers on top of the embedding layer, and return a model.

    An example of the `outputs_spec` argument is an OrderedDict specifying
    the names of the output layers, their respective: activation function,
    loss, and weight (multiplicative constant modifying the loss), e.g.: