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Update LFNA

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D-X-Y
2021-05-15 16:31:35 +08:00
parent 72f240bf0a
commit 5e766603be
1 changed files with 16 additions and 5 deletions
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21
exps/LFNA/lfna.py
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@@ -94,7 +94,10 @@ def main(args):
) )
optimizer = torch.optim.Adam( optimizer = torch.optim.Adam(
meta_model.parameters(), lr=args.init_lr, weight_decay=1e-5, amsgrad=True meta_model.parameters(),
lr=args.init_lr,
weight_decay=args.weight_decay,
amsgrad=True,
) )
lr_scheduler = torch.optim.lr_scheduler.MultiStepLR( lr_scheduler = torch.optim.lr_scheduler.MultiStepLR(
optimizer, optimizer,
@@ -137,7 +140,7 @@ def main(args):
) )
success, best_score = meta_model.save_best(-loss_meter.avg) success, best_score = meta_model.save_best(-loss_meter.avg)
if success: if success:
logger.log("Achieve the best with best_score = {:.3f}".format(best_score)) logger.log("Achieve the best with best-score = {:.5f}".format(best_score))
last_success_epoch = iepoch last_success_epoch = iepoch
save_checkpoint( save_checkpoint(
{ {
@@ -262,6 +265,12 @@ if __name__ == "__main__":
default=0.005, default=0.005,
help="The initial learning rate for the optimizer (default is Adam)", help="The initial learning rate for the optimizer (default is Adam)",
) )
parser.add_argument(
"--weight_decay",
type=float,
default=0.00001,
help="The weight decay for the optimizer (default is Adam)",
)
parser.add_argument( parser.add_argument(
"--meta_batch", "--meta_batch",
type=int, type=int,
@@ -274,11 +283,11 @@ if __name__ == "__main__":
default=5, default=5,
help="Enlarge the #iterations for an epoch", help="Enlarge the #iterations for an epoch",
) )
parser.add_argument("--epochs", type=int, default=1000, help="The total #epochs.") parser.add_argument("--epochs", type=int, default=10000, help="The total #epochs.")
parser.add_argument( parser.add_argument(
"--early_stop_thresh", "--early_stop_thresh",
type=int, type=int,
default=25, default=100,
help="The maximum epochs for early stop.", help="The maximum epochs for early stop.",
) )
parser.add_argument( parser.add_argument(
@@ -299,11 +308,13 @@ if __name__ == "__main__":
if args.rand_seed is None or args.rand_seed < 0: if args.rand_seed is None or args.rand_seed < 0:
args.rand_seed = random.randint(1, 100000) args.rand_seed = random.randint(1, 100000)
assert args.save_dir is not None, "The save dir argument can not be None" assert args.save_dir is not None, "The save dir argument can not be None"
args.save_dir = "{:}-d{:}_{:}_{:}-e{:}-env{:}".format( args.save_dir = "{:}-d{:}_{:}_{:}-lr{:}-wd{:}-e{:}-env{:}".format(
args.save_dir, args.save_dir,
args.hidden_dim, args.hidden_dim,
args.layer_dim, args.layer_dim,
args.time_dim, args.time_dim,
args.init_lr,
args.weight_decay,
args.epochs, args.epochs,
args.env_version, args.env_version,
) )