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)
