def make_folders(self):
log = create_logger()
if self.params.log:
try:
os.mkdir(self.params.folder_path)
except FileExistsError:
log.info('Folder already exists')
with open('saved_models/runs.html', 'a') as f:
f.writelines([
f'<div><a href="https://github.com/ebagdasa/'
f'backdoors/tree/{self.params.commit}">GitHub'
f'</a>, <span> <a href="http://gpu/'
f'{self.params.folder_path}">{self.params.name}_'
f'{self.params.current_time}</a></div>'
])
fh = logging.FileHandler(
filename=f'{self.params.folder_path}/log.txt')
formatter = logging.Formatter('%(asctime)s - %(name)s '
'- %(levelname)s - %(message)s')
fh.setFormatter(formatter)
log.addHandler(fh)
log.warning(f'Logging to: {self.params.folder_path}')
log.error(
f'LINK: <a href="https://github.com/ebagdasa/backdoors/tree/'
f'{self.params.commit}">https://github.com/ebagdasa/backdoors'
f'/tree/{self.params.commit}</a>')
with open(f'{self.params.folder_path}/params.yaml.txt', 'w') as f:
yaml.dump(self.params, f)
if self.params.tb:
wr = SummaryWriter(log_dir=f'runs/{self.params.name}')
self.tb_writer = wr
params_dict = self.params.to_dict()
table = create_table(params_dict)
self.tb_writer.add_text('Model Params', table)
criterion = nn.CrossEntropyLoss()
if helper.params['optimizer'] == 'SGD':
optimizer = optim.SGD(net.parameters(),
lr=lr,
momentum=momentum,
weight_decay=decay)
elif helper.params['optimizer'] == 'Adam':
optimizer = optim.Adam(net.parameters(), lr=lr, weight_decay=decay)
else:
raise Exception('Specify `optimizer` in params.yaml.')
scheduler = torch.optim.lr_scheduler.MultiStepLR(
optimizer, milestones=[0.5 * epochs, 0.75 * epochs], gamma=0.1)
table = create_table(helper.params)
writer.add_text('Model Params', table)
logger.info(table)
logger.info(helper.labels)
epoch = 0
# acc = test(net, epoch, "accuracy", helper.test_loader, vis=True)
for epoch in range(helper.start_epoch,
epochs): # loop over the dataset multiple times
if dp:
train_dp(helper.train_loader, net, optimizer, epoch)
else:
train(helper.train_loader, net, optimizer, epoch)
if helper.params['scheduler']:
scheduler.step()
main_acc = test(net, epoch, "accuracy", helper.test_loader, vis=True)
unb_acc_dict = dict()