def main():
"""Main script."""
parser = argparse.ArgumentParser()
parser.add_argument('--mode', required=True, help='train/test')
parser.add_argument('--gpu', required=True, help='gpu id')
parser.add_argument('--log', required=True, help='log directory')
parser.add_argument('--dataset',
required=True,
help='dataset name, msvd_qa/msrvtt_qa')
parser.add_argument('--config', required=True, help='config id')
args = parser.parse_args()
config = cfg.get('dmn_plus', args.dataset, args.config, args.gpu)
if args.dataset == 'msvd_qa':
dataset = dt.MSVDQA(config['train']['batch_size'],
config['preprocess_dir'])
question_type_dict = {
0: 'what',
2: 'who',
23: 'how',
96: 'when',
226: 'where'
}
elif args.dataset == 'msrvtt_qa':
dataset = dt.MSRVTTQA(config['train']['batch_size'],
config['preprocess_dir'])
question_type_dict = {
0: 'what',
3: 'who',
21: 'how',
61: 'when',
133: 'where'
}
if args.mode == 'train':
best_val_acc = -1
val_acc = 0
not_improved = -1
for epoch in range(0, 30):
if val_acc > best_val_acc:
best_val_acc = val_acc
not_improved = 0
else:
not_improved += 1
if not_improved == 10:
print('early stopping.')
break
train(epoch, dataset, config, args.log)
val_acc = val(epoch, dataset, config, args.log)
elif args.mode == 'test':
print('start test.')
test(dataset, config, args.log, question_type_dict)
def main():
"""Main script."""
parser = argparse.ArgumentParser()
parser.add_argument('--mode', required=True, help='train/test/predict')
parser.add_argument('--question', required=False)
parser.add_argument('--gpu', required=True, help='gpu id')
parser.add_argument('--log', required=True, help='log directory')
parser.add_argument('--dataset',
required=True,
help='dataset name, msvd_qa/msrvtt_qa')
parser.add_argument('--config', required=True, help='config id')
args = parser.parse_args()
config = cfg.get('gra', args.dataset, args.config, args.gpu)
if args.dataset == 'msvd_qa':
dataset = dt.MSVDQA(config['train']['batch_size'],
config['preprocess_dir'])
elif args.dataset == 'msrvtt_qa':
dataset = dt.MSRVTTQA(config['train']['batch_size'],
config['preprocess_dir'])
if args.mode == 'train':
best_val_acc = -1
val_acc = 0
not_improved = -1
for epoch in range(18, 30):
if val_acc > best_val_acc:
best_val_acc = val_acc
not_improved = 0
else:
not_improved += 1
if not_improved == 10:
print('early stopping.')
train(epoch, dataset, config, args.log)
val_acc = val(epoch, dataset, config, args.log)
elif args.mode == 'test':
print('start test.')
test(dataset, config, args.log)
elif args.mode == 'predict':
print('predicting ' + args.question)
predict(dataset, config, args.log, int(args.question))
def main():
"""Main script."""
parser = argparse.ArgumentParser()
parser.add_argument('--mode', default='test',
help='train/test')
parser.add_argument('--gpu', default='0',
help='gpu id')
parser.add_argument('--log', default='./log_esa',
help='log directory')
parser.add_argument('--dataset', choices=['msvd_qa', 'msrvtt_qa'], default='msrvtt_qa',
help='dataset name, msvd_qa/msrvtt_qa')
parser.add_argument('--config', default='0',
help='config id')
args = parser.parse_args()
config = cfg.get('esa', args.dataset, args.config, args.gpu)
if args.dataset == 'msvd_qa':
dataset = dt.MSVDQA(
config['train']['batch_size'], config['preprocess_dir'])
elif args.dataset == 'msrvtt_qa':
dataset = dt.MSRVTTQA(
config['train']['batch_size'], config['preprocess_dir'], config['model']['answer_num'])
if args.mode == 'train':
best_val_acc = -1
val_acc = 0
not_improved = -1
for epoch in range(0, 3000):
if val_acc > best_val_acc:
best_val_acc = val_acc
not_improved = 0
else:
not_improved += 1
if not_improved == 10:
print('early stopping.')
break
train(epoch, dataset, config, args.log)
val_acc = val(epoch, dataset, config, args.log)
elif args.mode == 'test':
print('start test.')
test(dataset, config, args.log)
