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()