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
