def initOutputDir(self):
if self.conf.output_dir != 'output':
LOG.logW("According deepvac standard, you should save model files to output directory.")
self.output_dir = '{}/{}'.format(self.conf.output_dir, self.branch)
LOG.logI('model save dir: {}'.format(self.output_dir))
if not os.path.exists(self.output_dir):
os.makedirs(self.output_dir)
def initOptimizer(self):
self.initSgdOptimizer()
LOG.logW(
"You should reimplement initOptimizer() to initialize self.optimizer, unless SGD is exactly what you need"
)
def initScheduler(self):
self.scheduler = torch.optim.lr_scheduler.StepLR(
self.optimizer, self.conf.lr_step, self.conf.lr_factor)
LOG.logW(
"You should reimplement initScheduler() to initialize self.scheduler, unless lr_scheduler.StepLR() is exactly what you need"
)
def initCriterion(self):
self.criterion = torch.nn.CrossEntropyLoss()
LOG.logW(
"You should reimplement initCriterion() to initialize self.criterion, unless CrossEntropyLoss() is exactly what you need"
)