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