def args(sub_parser: _SubParsersAction) -> None: sub_parser.add_argument('--weights', type=str, dest='weights', required=True, help='Required. Weights file path') sub_parser.add_argument('--input', type=str, dest='input', required=True, help='Required. Input images dir path') sub_parser.add_argument('--output', type=str, dest='output', required=True, help='Required. Output images dir path') sub_parser.add_argument('--batch-size', type=int, dest='batch_size', default=1, help='Default = 1. Batch Size for Testing.') sub_parser.add_argument('--gpu', action='store_true', dest='gpu', help="Default = False. Set if using gpu") sub_parser.set_defaults(gpu=False) sub_parser.add_argument('--input-shape', type=list, dest='input_shape', default=(256, 256, 3), help='Default = (256, 256, 3). Input Shape.')
def args(sub_parser: _SubParsersAction): # print("\n---------------------------------") # print("AdaS Train Args") # print("---------------------------------\n") # sub_parser.add_argument( # '-vv', '--very-verbose', action='store_true', # dest='very_verbose', # help="Set flask debug mode") # sub_parser.add_argument( # '-v', '--verbose', action='store_true', # dest='verbose', # help="Set flask debug mode") # sub_parser.set_defaults(verbose=False) # sub_parser.set_defaults(very_verbose=False) # sub_parser.add_argument( # '--beta', dest='beta', # default=0.8, type=float, # help="set beta hyper-parameter") # sub_parser.add_argument( # '--zeta', dest='zeta', # default=1.0, type=float, # help="set zeta hyper-parameter") # sub_parser.add_argument( # '-p', dest='p', # default=2, type=int, # help="set power (p) hyper-parameter") # sub_parser.add_argument( # '--init-lr', dest='init_lr', # default=3e-2, type=float, # help="set initial learning rate") # sub_parser.add_argument( # '--min-lr', dest='min_lr', # default=3e-2, type=float, # help="set minimum learning rate") sub_parser.add_argument( '--config', dest='config', default='config.yaml', type=str, help="Set configuration file path: Default = 'config.yaml'") sub_parser.add_argument( '--data', dest='data', default='.adas-data', type=str, help="Set data directory path: Default = '.adas-data'") sub_parser.add_argument( '--output', dest='output', default='.adas-output', type=str, help="Set output directory path: Default = '.adas-output'") sub_parser.add_argument( '--checkpoint', dest='checkpoint', default='.adas-checkpoint', type=str, help="Set checkpoint path: Default = '.adas-checkpoint/ckpt.pth'") sub_parser.add_argument( '--root', dest='root', default='.', type=str, help="Set root path of project that parents all others: Default = '.'") sub_parser.add_argument( '-r', '--resume', action='store_true', dest='resume', help="Flag: resume training from checkpoint") sub_parser.set_defaults(verbose=False)
def args(sub_parser: _SubParsersAction) -> None: sub_parser.add_argument('-vv', '--very-verbose', action='store_true', dest='very_verbose', help="Set flask debug mode") sub_parser.add_argument('-v', '--verbose', action='store_true', dest='verbose', help="Set flask debug mode") sub_parser.set_defaults(verbose=False) sub_parser.set_defaults(very_verbose=False)
def args(sub_parser: _SubParsersAction): # print("\n---------------------------------") # print("AdaS Train Args") # print("---------------------------------\n") # sub_parser.add_argument( # '-vv', '--very-verbose', action='store_true', # dest='very_verbose', # help="Set flask debug mode") # sub_parser.add_argument( # '-v', '--verbose', action='store_true', # dest='verbose', # help="Set flask debug mode") # sub_parser.set_defaults(verbose=False) # sub_parser.set_defaults(very_verbose=False) sub_parser.add_argument( '--config', dest='config', default='config.yaml', type=str, help="Set configuration file path: Default = 'config.yaml'") sub_parser.add_argument( '--data', dest='data', default='.adas-data', type=str, help="Set data directory path: Default = '.adas-data'") sub_parser.add_argument( '--output', dest='output', default='.adas-output', type=str, help="Set output directory path: Default = '.adas-output'") sub_parser.add_argument( '--checkpoint', dest='checkpoint', default='.adas-checkpoint', type=str, help="Set checkpoint directory path: Default = '.adas-checkpoint'") sub_parser.add_argument('--resume', dest='resume', default=None, type=str, help="Set checkpoint resume path: Default = None") # sub_parser.add_argument( # '-r', '--resume', action='store_true', # dest='resume', # help="Flag: resume training from checkpoint") sub_parser.add_argument( '--root', dest='root', default='.', type=str, help="Set root path of project that parents all others: Default = '.'") sub_parser.add_argument( '--save-freq', default=25, type=int, help='Checkpoint epoch save frequency: Default = 25') # sub_parser.set_defaults(resume=False) sub_parser.add_argument('--cpu', action='store_true', dest='cpu', help="Flag: CPU bound training: Default = False") sub_parser.set_defaults(cpu=False) sub_parser.add_argument('--gpu', default=0, type=int, help='GPU id to use: Default = 0') sub_parser.add_argument( '--multiprocessing-distributed', action='store_true', dest='mpd', help='Use multi-processing distributed training to launch ' 'N processes per node, which has N GPUs. This is the ' 'fastest way to use PyTorch for either single node or ' 'multi node data parallel training: Default = False') sub_parser.set_defaults(mpd=False) sub_parser.add_argument('--dist-url', default='tcp://127.0.0.1:23456', type=str, help="url used to set up distributed training:" + "Default = 'tcp://127.0.0.1:23456'") sub_parser.add_argument('--dist-backend', default='nccl', type=str, help="distributed backend: Default = 'nccl'") sub_parser.add_argument( '--world-size', default=-1, type=int, help='Number of nodes for distributed training: Default = -1') sub_parser.add_argument( '--rank', default=-1, type=int, help='Node rank for distributed training: Default = -1')
def args(sub_parser: _SubParsersAction) -> None: sub_parser.add_argument('--data', type=str, dest='data', required=True, help='Required. Dataset path') sub_parser.add_argument('--checkpoint', type=str, dest='checkpoint', required=True, help='Required. Checkpoint path') sub_parser.add_argument('--image-direction', type=ImageDirection.__getitem__, choices=ImageDirection.__members__.values(), dest='image_direction', required=True, help="Required. Image Direction") sub_parser.add_argument('--epochs', type=int, required=True, help='Required. Number of epochs to train for') sub_parser.add_argument('--log-dir', type=str, dest='log_dir', required=False, default=None, help='Default = checkpoint dir. Log dir path. ' + 'logs will be written to "args.checkpoint/logs"') sub_parser.add_argument('--batch-size', type=int, dest='batch_size', default=1, help='Default = 1. Batch Size for Training.') sub_parser.add_argument('--buffer-size', type=int, dest='buffer_size', default=400, help='Default = 400. Buffer Size for Training') sub_parser.add_argument('--lambda', type=int, dest='_lambda', default=100, help='Default = 100. Lambda value for Training') sub_parser.add_argument('--save-freq', type=int, dest='save_freq', default=20, help='Default = 20. Save every X number of epochs') sub_parser.add_argument('--input-shape', type=list, dest='input_shape', default=(256, 256, 3), help='Default = (256, 256, 3). Input Shape.') sub_parser.add_argument('--gpu', action='store_true', dest='gpu', help="Default = False. Set if using gpu") sub_parser.set_defaults(gpu=False) sub_parser.add_argument('--tensorboard', action='store_true', dest='tensorboard', help="Default = False. Set if using tensorboard") sub_parser.set_defaults(gpu=False) sub_parser.add_argument( '--eager', action='store_true', dest='eager', help="Default = False. Set if using eager execution") sub_parser.set_defaults(eager=False)