def main():
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--batch_size', type=int, default=50)
parser.add_argument('--topk', type=int, default=128)
parser.add_argument('--model',
type=str,
default='conv',
choices=['rn', 'baseline'])
parser.add_argument('--checkpoint_path', type=str)
parser.add_argument('--train_dir', type=str)
parser.add_argument('--dataset_path',
type=str,
default='Sort-of-CLEVR_default')
parser.add_argument('--data_id', nargs='*', default=None)
parser.add_argument('--name', type=str, default="some_model")
config = parser.parse_args()
path = os.path.join('./datasets', config.dataset_path)
if check_data_path(path):
import sort_of_clevr as dataset
else:
raise ValueError(path)
config.data_info = dataset.get_data_info()
config.conv_info = dataset.get_conv_info()
dataset_train, dataset_test = dataset.create_default_splits(path)
evaler = Evaler(config, dataset_test)
log.warning("dataset: %s", config.dataset_path)
evaler.eval_run()
def main():
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--batch_size', type=int, default=16)
parser.add_argument('--model',
type=str,
default='baseline',
choices=['rn', 'baseline'])
parser.add_argument('--prefix', type=str, default='default')
parser.add_argument('--checkpoint', type=str, default=None)
parser.add_argument('--dataset_path',
type=str,
default='Sort-of-CLEVR_default')
parser.add_argument('--learning_rate', type=float, default=2.5e-4)
parser.add_argument('--lr_weight_decay',
action='store_true',
default=False)
config = parser.parse_args()
path = os.path.join('./datasets', config.dataset_path)
if check_data_path(path):
import sort_of_clevr as dataset
else:
raise ValueError(path)
config.data_info = dataset.get_data_info()
config.conv_info = dataset.get_conv_info()
dataset_train, dataset_test = dataset.create_default_splits(path)
trainer = Trainer(config, dataset_train, dataset_test)
log.warning("dataset: %s, learning_rate: %f", config.dataset_path,
config.learning_rate)
trainer.train()
def main():
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--batch_size', type=int, default=64)
parser.add_argument('--model', type=str, default='rn', choices=['rn', 'baseline'])
parser.add_argument('--checkpoint_path', type=str)
parser.add_argument('--location', action='store_true')
parser.add_argument('--visualize', action='store_true')
parser.add_argument('--train_dir', type=str)
parser.add_argument('--dataset_path', type=str, default='')
parser.add_argument('--data_id', nargs='*', default=None)
config = parser.parse_args()
path = os.path.join('../DatasetCreation/VG', config.dataset_path)
if check_data_path(path):
import sort_of_clevr as dataset
else:
raise ValueError(path)
config.data_info = dataset.get_data_info()
config.conv_info = dataset.get_conv_info()
dataset_train, dataset_test = dataset.create_default_splits(path)
evaler = Evaler(config, dataset_test)
log.warning("dataset: %s", config.dataset_path)
evaler.eval_run()
def main():
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--batch_size', type=int, default=16 * 1)
parser.add_argument('--model',
type=str,
default='ilp',
choices=['rn', 'baseline'])
# parser.add_argument('--checkpoint_path', type=str,default='./train_dir/ilp-default-Sort-of-CLEVR_default_lr_0.0025-20190619-195552/model-32000')
# parser.add_argument('--checkpoint_path', type=str,default='./train_dir/ilp-default-Sort-of-CLEVR_default_lr_0.0025-20190619-115754/model-42000')
parser.add_argument(
'--checkpoint_path',
type=str,
default=
'./train_dir/ilp-default-Sort-of-CLEVR_default_lr_0.002-20190807-173045/model-80000'
)
parser.add_argument('--train_dir', type=str)
parser.add_argument('--dataset_path',
type=str,
default='Sort-of-CLEVR_default')
parser.add_argument('--data_id', nargs='*', default=None)
config = parser.parse_args()
path = os.path.join('./datasets', config.dataset_path)
if check_data_path(path):
import sort_of_clevr as dataset
else:
raise ValueError(path)
config.data_info = dataset.get_data_info()
config.conv_info = dataset.get_conv_info()
dataset_train, dataset_test = dataset.create_default_splits(path)
evaler = Evaler(config, dataset_test)
# qs1=[]
# qs2=[]
# ans=[]
# for id in dataset_test._ids:
# dt = dataset_train.get_data(id)
# qs1.append( np.argmax(dt[1][:6]) )
# qs2.append( np.argmax(dt[1][6:]) )
# ans.append( np.argmax(dt[2]) )
log.warning("dataset: %s", config.dataset_path)
evaler.eval_run()