validate_start_path=validate_start_path,
weights_path=weights_path,
var_filename=var_filename)
# model creation
model = Mod.get_model(filters=filters, le=learn_rate, decay=decay_rate)
weights_loaded = False
if load_weights:
weights_loaded = Mod.load_weights()
if not weights_loaded:
Mod.save_weights()
Mod.plot_loss(500)
Mod.check_performance(train_generator, times=check_perf_times)
callbacks = md.Callbacks(ModelClass=Mod,
save_modulo_epochs=save_modulo,
printDecay=printDecay,
collectLoss=collectLoss)
# go
if validate:
Mod.validate(validateMode=mode,
preprocessFunc=validatePreprocessFunc,
draw=draw,
onlyWithMetric=onlyWithMetric,
onlyWithoutMetric=onlyWithoutMetric,
sumTimes=sumTimes)
else:
for loop in range(total_ep):
i = loop + 1
print("ep:" + str(i))
Mod = md.Models(rows, cols, mode=mode, channels=channels_in, show_function=show_function, read_func=read_function,
validate_path_provider_func=validate_path_provider_func, validate_start_path=validate_start_path,
weights_path=weights_path, var_filename=var_filename)
# model creation
model = Mod.get_model(filters=filters, le=learn_rate, decay=decay_rate)
weights_loaded = False
if load_weights:
weights_loaded = Mod.load_weights()
if not weights_loaded:
Mod.save_weights()
Mod.check_performance(train_generator, times=check_perf_times, metrics= metrics)
callbacks = md.Callbacks(ModelClass=Mod, save_modulo_epochs=save_modulo, printDecay=printDecay, collectLoss=collectLoss, message='Model no.: '+str(j+1))
# go
if validate:
results = Mod.validate(validateMode=mode, preprocessFunc=validatePreprocessFunc, draw=draw, onlyWithMetric=onlyWithMetric,
onlyWithoutMetric=onlyWithoutMetric, sumTimes=sumTimes, metrics=metrics, validTimes=6, validName='Zanik', weightsTimesValids=100)
sum = list(map(add, sum, results))
else:
for loop in range(total_ep):
i = loop + 1
print("ep:" + str(i))
model.fit_generator(train_generator, steps_per_epoch=steps, epochs=ep, callbacks=[callbacks])
if i % loop_modulo == 0:
Mod.check_performance(train_generator, times=check_perf_times_in_loop)