def parse(): parser = argparse.ArgumentParser(description="DensetNet - 2020 by marksein07") #parser.add_argument('--optimizer') parser.add_argument('--memory_efficient', type=float, default=0.9, help='memory efficient on DenseNet') parser.add_argument('--bias', type=float, default=0.9, help='Apply bias on DenseNet') parser.add_argument('--num_init_features', type=int, default=16, help='init features number') parser.add_argument('--compression_rate', type=float, default=0.5, help='DenseNet compression rate') parser.add_argument('--dropout_rate', type=float, default=0.2, help='dropout rate') parser.add_argument('--bottleneck_size', type=int, default=4, help='DenseNet bottleneck size') parser.add_argument('--layer_num', type=int, default=100, help='DenseNet layers number') parser.add_argument('--growth_rate', type=int, default=12, help='DenseNet growth rate') parser.add_argument('--batch_size', type=int,default=64, help='traing and testing batch size') parser.add_argument('--learning_rate', type=float, default=1e-1, help='optimizer learning rate') parser.add_argument('--weight_decay', type=float, default=1e-4, help='optimizer L2 penalty') parser.add_argument('--momentum', type=float, default=0.9, help='optimizer momentum') parser.add_argument('--cuda', type=str, default='0', help='GPU Index for training') parser.add_argument('--log', type=str, default='../result/log', help='tensorboard log directory') parser.add_argument('--result', type=str, default='../result', help='experiment result') parser.add_argument('--preceed', type=bool, default=False, help='whether load a pretrain model') parser.add_argument('--training_epoch', type=int, default=300, help='total training epoch') optimizer_group = parser.add_mutually_exclusive_group() optimizer_group.add_argument('--SGD', action='store_true', default=True, help='Choose SGD as optimizer') optimizer_group.add_argument('--Adam', action='store_true', default=False, help='Choose Adam as optimizer') optimizer_group.add_argument('--Adagrad', action='store_true', default=False, help='Choose Adagrad as optimizer') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="Anime ACGAN") parser.add_argument('--uid', type=str, help='training uid', required=True) parser.add_argument('--train_path', type=str, default='data', help='training data path') parser.add_argument('--gen_lr', type=float, default=0.00015, help='learning rate of generator') parser.add_argument('--dis_lr', type=float, default=0.0002, help='learning rate of discriminator') parser.add_argument('--batch_size', type=int, default=128, help='batch size for training') parser.add_argument('--epochs', type=int, default=100000, help='epochs for training') parser.add_argument('--latent', type=int, default=100, help='latent size') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="ADL HW3") parser.add_argument('--env_name', default=None, help='environment name') parser.add_argument('--train_pg', action='store_true', help='whether train policy gradient') parser.add_argument('--train_dqn', action='store_true', help='whether train DQN') parser.add_argument('--test_pg', action='store_true', help='whether test policy gradient') parser.add_argument('--test_dqn', action='store_true', help='whether test DQN') parser.add_argument('--video_dir', default=None, help='output video directory') parser.add_argument('--do_render', action='store_true', help='whether render environment') parser.add_argument('--plot_dqn', type=int, help='1: learning curve 2: hyperparamters 3: improvement') parser.add_argument('--plot_pg', type=int, help='1: learning curve 3: improvement') parser.add_argument('--env-name', type=str, default='CartPole-v0') parser.add_argument('--max-steps', type=int, default=200, metavar='N') parser.add_argument('--num-episodes', type=int, default=1000, metavar='N') parser.add_argument('--num-trajs', type=int, default=10, metavar='N') parser.add_argument('--gamma', type=float, default=0.99, metavar='G') parser.add_argument('--lr', type=float, default=1e-3, metavar='G') parser.add_argument('--hidden_layer', type=int, default=128, metavar='N') parser.add_argument('--seed', type=int, default=777, metavar='N',) parser.add_argument('--reinforce', action ='store_true', help='Use REINFORCE instead of importance sampling') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser( description="Discourse Parsing with shfit reduce method") parser.add_argument('--make_dataset', action='store_true', help='whether make training dataset') parser.add_argument('--train_edu', action='store_true', help='whether train edu segmenter') parser.add_argument('--train_trans', action='store_true', help='whether train shift & reduce parsing') parser.add_argument('--train_rlat', action='store_true', help='whether train labeling for merged node') parser.add_argument('--test', action='store_true', help='whether test performance') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="PG & Actor-Critic") parser.add_argument('--test_pg', action='store_true', help='whether test policy gradient') parser.add_argument('--video_dir', default=None, help='output video directory') parser.add_argument('--do_render', action='store_true', help='whether render environment') parser.add_argument('--test_pg_model_path', type=str, default="pretrained_model/pg_model.h5", help='') parser.add_argument('--save_summary_path', type=str, default="pg_summary/", help='') parser.add_argument('--save_network_path', type=str, default="saved_pg_networks/", help='') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser( description="MLDS&ADL Final Project", formatter_class=argparse.ArgumentDefaultsHelpFormatter) parser.add_argument( '--env_name', default='SeaquestNoFrameskip-v4', help= 'environment name - SeaquestNoFrameskip-v4, EnduroNoFrameskip-v4, SpaceInvadersNoFrameskip-v4' ) parser.add_argument('--demo_file', default=None, help='demo file') parser.add_argument('--train', action='store_true', help='whether train or not') parser.add_argument('--test', action='store_true', help='whether test or not') parser.add_argument('--type', default='human', help='human, double, dueling, dqfd') parser.add_argument('--video_dir', default=None, help='output video directory') parser.add_argument('--do_render', action='store_true', help='whether render environment') parser.add_argument('--model_path', default=None, help='model path') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="DQN") parser.add_argument('--test_dqn', action='store_true', help='whether test DQN') parser.add_argument('--video_dir', default=None, help='output video directory') parser.add_argument('--do_render', action='store_true', help='whether render environment') parser.add_argument( '--gbp', action='store_true', help='visualize what the network learned with Guided backpropagation') parser.add_argument('--gradCAM', action='store_true', help='visualize what the network learned with GradCAM') parser.add_argument( '--gbp_GradCAM', action='store_true', help='visualize what the network learned with Guided GradCAM') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="ADL HW3") parser.add_argument('--env_name', default=None, help='environment name') parser.add_argument('--train_pg', action='store_true', help='whether train policy gradient') parser.add_argument('--train_dqn', action='store_true', help='whether train DQN') parser.add_argument('--test_pg', action='store_true', help='whether test policy gradient') parser.add_argument('--test_dqn', action='store_true', help='whether test DQN') parser.add_argument('--video_dir', default=None, help='output video directory') parser.add_argument('--do_render', action='store_true', help='whether render environment') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="Video to Text Model") parser.add_argument('--uid', type=str, help='training uid', required=True) parser.add_argument('--train_path', default='data/training_data', type=str, help='training data path') parser.add_argument('--test_path', default='data/testing_data', type=str, help='test data path') parser.add_argument('--learning_rate', type=float, default=0.0007, help='learning rate for training') parser.add_argument('--batch_size', type=int, default=320, help='batch size for training') parser.add_argument('--epoch', type=int, default=100, help='epochs for training') parser.add_argument('--test', action='store_true', help='use this flag for testing') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser( description= "CDTB discourse parsing with shfit reduce method and use PDTB-style CDTB as augmentation data" ) parser.add_argument('--make_dataset', action='store_true', help='whether make training dataset') parser.add_argument('--train_edu', action='store_true', help='whether train edu segmenter') parser.add_argument('--train_trans', action='store_true', help='whether train shift & reduce parser') parser.add_argument('--train_rlat', action='store_true', help='whether train relation and center classifier') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="MLDS 2018 HW4") parser.add_argument('--env_name', default=None, help='environment name') parser.add_argument('--train_pg', action='store_true', help='whether train policy gradient') parser.add_argument('--train_pg_improved', action='store_true', help='whether train PPO') parser.add_argument('--train_dqn', action='store_true', help='whether train DQN') parser.add_argument('--train_pong_ac', action='store_true', help='whether train pong ac') parser.add_argument('--train_break_ac', action='store_true', help='whether train break ac') parser.add_argument('--train_pong_ac_improved', action='store_true', help='whether train pong ac improved') parser.add_argument('--train_break_ac_improved', action='store_true', help='whether train break ac improved') parser.add_argument('--test_pg', action='store_true', help='whether test policy gradient') parser.add_argument('--test_pg_improved', action='store_true', help='whether test PPO') parser.add_argument('--test_dqn', action='store_true', help='whether test DQN') parser.add_argument('--test_dqn_improved', action='store_true', help='whether test Dueling DQN') parser.add_argument('--train_dqn_improved', action='store_true', help='whether train Dueling DQN') parser.add_argument('--test_ddqn', action='store_true', help='whether test DDQN') parser.add_argument('--train_ddqn', action='store_true', help='whether train DDQN') parser.add_argument('--test_dddqn', action='store_true', help='whether test DDDQN') parser.add_argument('--train_dddqn', action='store_true', help='whether train DDDQN') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="DS595/CS525 RL Project 3") parser.add_argument('--test_dqn', action='store_true', help='whether test DQN') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="Reinforment Learning - Play Ping-Pong") parser.add_argument('--test', action='store_true', help='whether test policy gradient') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="p2") parser.add_argument('--machine', default="Mac", help='environment name') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="MLDS 2018 HW4") parser.add_argument('--test_pg', action='store_true', help='whether test policy gradient') parser.add_argument('--test_dqn', action='store_true', help='whether test DQN') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser() parser.add_argument('--env_name', default=None, help='environment name') parser.add_argument('--train_dqn', action='store_true', help='whether train DQN') parser.add_argument('--test_dqn', action='store_true', help='whether test DQN') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description='CN_HW2 Sender') parser.add_argument('source', type=str) try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() print('Argument list:') print(args) return args
def parse(self): parser = argparse.ArgumentParser(description="chatbot") parser.add_argument('--train', action='store_true', help='whether train') parser.add_argument('--test', action='store_true', help='whether test') parser.add_argument('--model_restore', action='store_true', help='whether restore the model') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description='CN_HW2 Receiver') parser.add_argument('dest', type=str) parser.add_argument('--buffer_size', type=int, default=32) try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() print('Argument list:') print(args) return args
def parse(): parser = argparse.ArgumentParser(description="Slither.io AI bot") parser.add_argument('--train_pg', action='store_true', help='whether train policy gradient') parser.add_argument('--train_dqn', action='store_true', help='whether train DQN') parser.add_argument('--train_ac', action='store_true', help='whether train Actor-Critic') parser.add_argument('--train_a2c', action='store_true', help='whether train A2C') parser.add_argument('--test_pg', action='store_true', help='whether test policy gradient') parser.add_argument('--test_dqn', action='store_true', help='whether test DQN') parser.add_argument('--test_ac', action='store_true', help='whether test Actor-Critic') parser.add_argument('--test_a2c', action='store_true', help='whether test A2C') parser.add_argument('--video_dir', default='records', help='output video directory') parser.add_argument('--do_render', action='store_true', help='whether render environment') parser.add_argument('--remotes', type=int, default=1, help='Number of envs.') parser.add_argument('--channels', default=3, help='observation input channels') parser.add_argument('--action_space', type=int, default=12, help='snake moving action space') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="DS595/CS525 RL Project 3") parser.add_argument('--env_name', default=None, help='environment name') parser.add_argument('--train_dqn', action='store_true', help='whether train DQN') parser.add_argument('--test_dqn', action='store_true', help='whether test DQN') parser.add_argument('--max_episodes', type=int, default=10_000_000) parser.add_argument('--gamma', type=float, default=0.99) parser.add_argument('--eps', type=float, default=1.0) parser.add_argument('--eps_min', type=float, default=0.1) parser.add_argument('--eps_decay_window', type=int, default=1_000_000) parser.add_argument('--window', type=int, default=100) parser.add_argument('--capacity', type=int, default=10_000) parser.add_argument('--mem_init_size', type=int, default=5_000) parser.add_argument('--batch_size', type=int, default=32) parser.add_argument('--target_update', type=int, default=5_000) parser.add_argument('--learn_freq', type=int, default=4) parser.add_argument('--gc_freq', type=int, default=1000) parser.add_argument('--load_dir', type=str, default='') parser.add_argument('--save_freq', type=int, default=1000) parser.add_argument('--disp_freq', type=int, default=100) parser.add_argument('--optimizer_eps', type=int, default=0.001) parser.add_argument('--device', type=str, default='cpu') parser.add_argument('--save_dir', type=str, default='checkpoint') parser.add_argument('--use_pri_buffer', type=bool, default=False) parser.add_argument('--pri_beta_start', type=float, default=0.4) parser.add_argument('--pri_beta_decay', type=float, default=100_000) parser.add_argument('--use_double_dqn', type=bool, default=True) parser.add_argument('--restore_only_weights', type=bool, default=True) parser.add_argument('--use_bnorm', type=bool, default=False) parser.add_argument('--use_dueling', type=bool, default=False) parser.add_argument('--use_crnn', type=bool, default=False) parser.add_argument('--lr', type=int, default=1e-3) parser.add_argument("--lr_scheduler", type=bool, default=False) parser.add_argument("--lr_min", type=float, default=1e-4) parser.add_argument("--lr_decay", type=float, default=0.999) parser.add_argument("--lr_decay_step", type=float, default=100) parser.add_argument("--tb_summary", type=bool, default=True) try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() torch.set_default_tensor_type('torch.cuda.FloatTensor' if args.device == "cuda" else 'torch.FloatTensor') return args
def parse(): parser = argparse.ArgumentParser(description="DQN: Atari 2600") parser.add_argument('--env_name', default=None, help='environment name') parser.add_argument('--train_dqn', action='store_true', help='whether train DQN') parser.add_argument('--test_dqn', action='store_true', help='whether test DQN') parser.add_argument('--do_render', action='store_true', help='whether display video in testing mode') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description='CN_HW2 Agent') parser.add_argument('--loss_rate', type=float, default=0.2) parser.add_argument('--forwardIP', type=str, default='127.0.0.1') parser.add_argument('--forwardPort', type=int, default=6666) try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() print('Argument list:') print(args) return args
def parse(): parser = argparse.ArgumentParser(description="expectation learning") parser.add_argument('--env_name', default=None, help='environment name') parser.add_argument('--train_exp', action='store_true', help='train or test') parser.add_argument('--test_exp', action='store_true', help='train or test') parser.add_argument('--keep', action='store_true', help='whether use the trained model') parser.add_argument('--batch_size', default=1, help='batch_size') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="DS595/CS525 RL Project 3") parser.add_argument('--env_name', default=None, help='environment name') parser.add_argument('--train_dqn', action='store_true', help='whether train DQN') parser.add_argument('--test_dqn', action='store_true', help='whether test DQN') parser.add_argument('--cont', action='store_true', help='whether continue DQN') parser.add_argument('--n_heads', default=1, help='whether n_heads') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="MLDS&ADL HW3") parser.add_argument('--test_pg', action='store_true', help='whether test policy gradient') parser.add_argument('--test_dqn', action='store_true', help='whether test DQN') parser.add_argument('--model', type=str, default='dqn_final.model', help='model name') parser.add_argument('--env_id',type=str,default='BreakoutNoFrameskip-v4' ,help='enviornment name') parser.add_argument('--video_dir', default=None, help='output video directory') parser.add_argument('--do_render', action='store_true', help='whether render environment') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="MLDS 2018 HW4") parser.add_argument('--env_name', default=None, help='environment name') parser.add_argument('--train_pg', action='store_true', help='whether train policy gradient') parser.add_argument('--train_dqn', action='store_true', help='whether train DQN') parser.add_argument('--test_pg', action='store_true', help='whether test policy gradient') parser.add_argument('--test_dqn', action='store_true', help='whether test DQN') parser.add_argument('--train_ac', action='store_true', help='whether train ActorCritic') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(self): parser = argparse.ArgumentParser(description="MLDS 2018 HW4") parser.add_argument('--policy_1', default=None, help='data type') parser.add_argument('--policy_2', default=None, help='data type') parser.add_argument('--look', action='store_true', help='set to the main policy') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser(description="Plant classifier") parser.add_argument('--uid', type=str, help='training uid', required=True) parser.add_argument('--train_path',type=str, default='data/train', help='training data path') parser.add_argument('--valid_path',type=str, default='data/valid', help='valid data path') parser.add_argument('--train_resnet', default = True, action='store_true', help='whether train on ResNet50') parser.add_argument('--train_inception', action='store_true', help='whether train on InceptionResNetV2') parser.add_argument('--learning_rate', type=float, default=0.00008, help='learning rate for training') parser.add_argument('--batch_size', type=int, default=64, help='batch size for training') parser.add_argument('--epoch', type=int, default=100, help='epochs for training') parser.add_argument('--img_size', type=int, default=224, help='img width, height size') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args
def parse(): parser = argparse.ArgumentParser( description="Discourse Parsing with shfit reduce method") parser.add_argument('--input_file', type=str, default='None', help='path of input file') parser.add_argument('--output_file', type=str, default='None', help='path of output file') try: from argument import add_arguments parser = add_arguments(parser) except: pass args = parser.parse_args() return args