def getModel(name, nb_res_units, dayInfo_dim): if MODELNAME == 'STResNet': c_dim = (HEIGHT, WIDTH, nb_channel, len_c) p_dim = (HEIGHT, WIDTH, nb_channel, len_p) t_dim = (HEIGHT, WIDTH, nb_channel, len_t) model = stresnet(c_dim=c_dim, p_dim=p_dim, t_dim=t_dim, residual_units=nb_res_units, dayInfo_dim=dayInfo_dim) #model.summary() return model else: return None
def build_model(external_dim): c_conf = (len_closeness, nb_flow, map_height, map_width) if len_closeness > 0 else None p_conf = (len_period, nb_flow, map_height, map_width) if len_period > 0 else None t_conf = (len_trend, nb_flow, map_height, map_width) if len_trend > 0 else None model = stresnet(c_conf=c_conf, p_conf=p_conf, t_conf=t_conf, external_dim=external_dim, nb_residual_unit=nb_residual_unit) adam = Adam(lr=lr) model.compile(loss='mse', optimizer=adam, metrics=[metrics.rmse]) model.summary() # from keras.utils.visualize_util import plot from keras.utils.vis_utils import plot_model plot_model(model, to_file='model.png', show_shapes=True) return model