def train_args(sub_parser: _SubParsersAction) -> None: sub_parser.add_argument( '--config', dest='config', default='config.yaml', type=str, help="Set configuration file path: Default = 'config.yaml'")
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) -> None: sub_parser.add_argument('--data-source', type=str.lower, dest='data_source', choices=['landsat'], required=True, help="Required. Data source for download.") sub_parser.add_argument( '--instance-id', type=str, default='instance_id.txt', dest='instance_id', help="Default: instance_id.txt. File name of instance id for \n" + "data-set-specific API Accessor") sub_parser.add_argument('--height-file', type=str, default='data/shp/2019_height.shp', dest='height_file', help="") sub_parser.add_argument( '--shopping-list', type=str, default='shopping_list.json', dest='shopping_list', help="Default: shopping_list.json. File name of settings and \n" + "API demands for data-set-specific download.\n" + "See \"core/src/uhinet/backend/data/shopping_list_example.txt\"\n" + "for an example.\n" f"Valid keys are as follows:\n" + " - centers: a dict of centers coordinates and id. Subkeys are \n" + " {name, lat, lon}.\n" + " - year_from: Start date to grab data from.\n" + " - year_to: Start date to grab data to.\n" + " - image_size: Tuple of image size in format (height, width)\n" + " - layers: List of layers from Landsat. Valid = [LST, RGB]\n" + " - cloud_coverage_percentage: Float betwen [0, 1] for \n" + " cloud coverage percentag\n" + " - spatial_resolution: Spatial resolution of images. Used in\n" + " combination with \\centers\\ and \n" + " \\image_size\\ to generate images. Spatial\n" + " resolution defines how many metres a pixel\n" + " represents.") sub_parser.add_argument( '--save-to', type=str, default='data/', dest='save_to', help="Default: 'data-download/'. Directory to save images to.")
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): # 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 add_shared_args(self, parser: _SubParsersAction, start: bool): parser.add_argument( "--train_dataset", "-t", required=start, help="Path to training dataset. This can be either a hdf5 file generated by " + "'dataset_tool_h5.py' or a folder of images. Note that images smaller than " + "the patch size will be padded using reflection when a folder is used.", ) parser.add_argument( "--validation_dataset", "-v", help="Path to validation dataset. This can be either a hdf5 file generated by " + "'dataset_tool_h5.py' or a folder of images.", ) parser.add_argument( "--iterations", "-i", required=start, type=int, help="Number of iterations (input images) to train for.", ) parser.add_argument( "--eval_interval", type=int, help="Number of iterations between evaluations. Should be divisible by " + "training batch size.", ) parser.add_argument( "--checkpoint_interval", type=int, help="Number of iterations between saving checkpoints. Should be divisible by " + "training batch size.", ) parser.add_argument( "--print_interval", type=int, help="Number of iterations between printing ongoing results to command line and " + "Tensorboard, should be divisible by training batch size.", ) parser.add_argument( "--train_batch_size", type=int, help="Batch size to use for training images.", ) parser.add_argument( "--validation_batch_size", type=int, help="Batch size to use for validation images.", ) parser.add_argument( "--patch_size", type=int, help="Patch size to use for training (square).", )
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)
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.')