def _data_loader(self):
train_trans = dlib.get_train_augmentations()
test_trans = dlib.get_test_augmentations()
df_train = pd.read_csv(self.args.train_file)
df_test = pd.read_csv(self.args.test_file)
if self.args.is_debug:
df_train = df_train.sample(frac=1.0).iloc[:2 *
self.args.batch_size, :]
df_test = df_test.sample(frac=1.0).iloc[:2 *
self.args.batch_size, :]
print('### Debug mode was going ###')
labels = list(df_train.target.values)
sampler = BalanceClassSampler(labels, mode="upsampling")
self.data['train_loader'] = DataLoader(dlib.DataBase(
df_train, self.args.data_path, train_trans),
batch_size=self.args.batch_size,
sampler=sampler)
self.data['test_loader'] = DataLoader(
dlib.DataBase(df_test, self.args.data_path, test_trans),
batch_size=self.args.batch_size, \
shuffle=False,
drop_last=False)
print('Data loading was finished ...')
def _data_loader(self):
self.data['train'] = DataLoader(
dlib.DataBase(self.args),
batch_size=self.args.batch_size, \
shuffle=True,
num_workers=self.args.workers)
self.data['lfw'] = DataLoader(
dlib.VerifyBase(self.args, benchmark = 'lfw'),
batch_size=self.args.batch_size // 2, \
num_workers=self.args.workers,
drop_last=False,
collate_fn=self.collate_fn_1v1)
print('Data loading was finished ...')
