| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354 |
- import os
- from cvargparse import GPUParser, Arg
- from chainer_addons.links import PoolingType
- from finetune.parser import default_factory
- def parse_args():
- parser = GPUParser(default_factory([
- PoolingType.as_arg("pooling",
- help_text="type of pre-classification pooling"),
- Arg("--n_components", type=int, default=1,
- help="Number of mixtures"),
- Arg("--alpha", type=float, default=0.99,
- help="EM update factor"),
- Arg("--fv_insize", type=float, default=256,
- help="input size for the FVE Layer"),
- # Arg("--normalize", action="store_true",
- # help="normalize features after cbil- or alpha-poolings"),
- # Arg("--subset", "-s", type=int, nargs="*", default=[-1], help="select specific classes"),
- # Arg("--no_sacred", action="store_true", help="do save outputs to sacred"),
- # Arg("--use_parts", action="store_true",
- # help="use parts, if present"),
- # Arg("--simple_parts", action="store_true",
- # help="use simple parts classifier, that only concatenates the features"),
- # Arg("--no_global", action="store_true",
- # help="use parts only, no global feature"),
- # Arg("--parts_in_bb", action="store_true", help="take only uniform regions where the centers are inside the bounding box"),
- # Arg("--rnd_select", action="store_true", help="hide random uniform regions of the image"),
- # Arg("--recurrent", action="store_true", help="observe all parts in recurrent manner instead of the whole image at once"),
- # ## AlphaPooling options
- # Arg("--init_alpha", type=int, default=1, help="initial parameter for alpha pooling"),
- # Arg("--kappa", type=float, default=1., help="Learning rate factor for alpha pooling"),
- # Arg("--switch_epochs", type=int, default=0, help="train alpha pooling layer and the rest of the network alternating")
- ])
- )
- parser.init_logger()
- return parser.parse_args()
|
