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Fix black issues

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This commit is contained in:
D-X-Y 2021-05-17 10:31:26 +08:00
parent 06fe246d82
commit b11cfe263d
8 changed files with 106 additions and 28 deletions
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15
exps/LFNA/basic-his.py
View File

@ -161,7 +161,10 @@ if __name__ == "__main__":
help="The synthetic enviornment version.",
)
parser.add_argument(
"--hidden_dim", type=int, required=True, help="The hidden dimension.",
"--hidden_dim",
type=int,
required=True,
help="The hidden dimension.",
)
parser.add_argument(
"--init_lr",
@ -170,10 +173,16 @@ if __name__ == "__main__":
help="The initial learning rate for the optimizer (default is Adam)",
)
parser.add_argument(
"--batch_size", type=int, default=512, help="The batch size",
"--batch_size",
type=int,
default=512,
help="The batch size",
)
parser.add_argument(
"--epochs", type=int, default=1000, help="The total number of epochs.",
"--epochs",
type=int,
default=1000,
help="The total number of epochs.",
)
parser.add_argument(
"--srange", type=str, required=True, help="The range of models to be evaluated"

20
exps/LFNA/basic-maml.py
View File

@ -41,7 +41,10 @@ class MAML:
)
self.meta_lr_scheduler = torch.optim.lr_scheduler.MultiStepLR(
self.meta_optimizer,
milestones=[int(epochs * 0.8), int(epochs * 0.9),],
milestones=[
int(epochs * 0.8),
int(epochs * 0.9),
],
gamma=0.1,
)
self.inner_lr = inner_lr
@ -194,7 +197,10 @@ if __name__ == "__main__":
help="The synthetic enviornment version.",
)
parser.add_argument(
"--hidden_dim", type=int, default=16, help="The hidden dimension.",
"--hidden_dim",
type=int,
default=16,
help="The hidden dimension.",
)
parser.add_argument(
"--meta_lr",
@ -224,10 +230,16 @@ if __name__ == "__main__":
help="The gap between prev_time and current_timestamp",
)
parser.add_argument(
"--meta_batch", type=int, default=64, help="The batch size for the meta-model",
"--meta_batch",
type=int,
default=64,
help="The batch size for the meta-model",
)
parser.add_argument(
"--epochs", type=int, default=2000, help="The total number of epochs.",
"--epochs",
type=int,
default=2000,
help="The total number of epochs.",
)
parser.add_argument(
"--early_stop_thresh",

15
exps/LFNA/basic-prev.py
View File

@ -149,7 +149,10 @@ if __name__ == "__main__":
help="The synthetic enviornment version.",
)
parser.add_argument(
"--hidden_dim", type=int, required=True, help="The hidden dimension.",
"--hidden_dim",
type=int,
required=True,
help="The hidden dimension.",
)
parser.add_argument(
"--init_lr",
@ -164,10 +167,16 @@ if __name__ == "__main__":
help="The gap between prev_time and current_timestamp",
)
parser.add_argument(
"--batch_size", type=int, default=512, help="The batch size",
"--batch_size",
type=int,
default=512,
help="The batch size",
)
parser.add_argument(
"--epochs", type=int, default=300, help="The total number of epochs.",
"--epochs",
type=int,
default=300,
help="The total number of epochs.",
)
parser.add_argument(
"--workers",

15
exps/LFNA/basic-same.py
View File

@ -149,7 +149,10 @@ if __name__ == "__main__":
help="The synthetic enviornment version.",
)
parser.add_argument(
"--hidden_dim", type=int, required=True, help="The hidden dimension.",
"--hidden_dim",
type=int,
required=True,
help="The hidden dimension.",
)
parser.add_argument(
"--init_lr",
@ -158,10 +161,16 @@ if __name__ == "__main__":
help="The initial learning rate for the optimizer (default is Adam)",
)
parser.add_argument(
"--batch_size", type=int, default=512, help="The batch size",
"--batch_size",
type=int,
default=512,
help="The batch size",
)
parser.add_argument(
"--epochs", type=int, default=300, help="The total number of epochs.",
"--epochs",
type=int,
default=300,
help="The total number of epochs.",
)
parser.add_argument(
"--workers",

30
exps/LFNA/lfna-debug-hpnet.py
View File

@ -62,7 +62,10 @@ def main(args):
)
lr_scheduler = torch.optim.lr_scheduler.MultiStepLR(
optimizer,
milestones=[int(args.epochs * 0.8), int(args.epochs * 0.9),],
milestones=[
int(args.epochs * 0.8),
int(args.epochs * 0.9),
],
gamma=0.1,
)
@ -170,7 +173,10 @@ if __name__ == "__main__":
help="The synthetic enviornment version.",
)
parser.add_argument(
"--hidden_dim", type=int, required=True, help="The hidden dimension.",
"--hidden_dim",
type=int,
required=True,
help="The hidden dimension.",
)
#####
parser.add_argument(
@ -180,7 +186,10 @@ if __name__ == "__main__":
help="The initial learning rate for the optimizer (default is Adam)",
)
parser.add_argument(
"--meta_batch", type=int, default=64, help="The batch size for the meta-model",
"--meta_batch",
type=int,
default=64,
help="The batch size for the meta-model",
)
parser.add_argument(
"--early_stop_thresh",
@ -189,13 +198,22 @@ if __name__ == "__main__":
help="The maximum epochs for early stop.",
)
parser.add_argument(
"--epochs", type=int, default=2000, help="The total number of epochs.",
"--epochs",
type=int,
default=2000,
help="The total number of epochs.",
)
parser.add_argument(
"--per_epoch_step", type=int, default=20, help="The total number of epochs.",
"--per_epoch_step",
type=int,
default=20,
help="The total number of epochs.",
)
parser.add_argument(
"--device", type=str, default="cpu", help="",
"--device",
type=str,
default="cpu",
help="",
)
# Random Seed
parser.add_argument("--rand_seed", type=int, default=-1, help="manual seed")

30
exps/LFNA/lfna.py
View File

@ -101,7 +101,10 @@ def main(args):
)
lr_scheduler = torch.optim.lr_scheduler.MultiStepLR(
optimizer,
milestones=[int(args.epochs * 0.8), int(args.epochs * 0.9),],
milestones=[
int(args.epochs * 0.8),
int(args.epochs * 0.9),
],
gamma=0.1,
)
logger.log("The base-model is\n{:}".format(base_model))
@ -240,13 +243,22 @@ if __name__ == "__main__":
help="The synthetic enviornment version.",
)
parser.add_argument(
"--hidden_dim", type=int, default=16, help="The hidden dimension.",
"--hidden_dim",
type=int,
default=16,
help="The hidden dimension.",
)
parser.add_argument(
"--layer_dim", type=int, default=16, help="The layer chunk dimension.",
"--layer_dim",
type=int,
default=16,
help="The layer chunk dimension.",
)
parser.add_argument(
"--time_dim", type=int, default=16, help="The timestamp dimension.",
"--time_dim",
type=int,
default=16,
help="The timestamp dimension.",
)
#####
parser.add_argument(
@ -262,7 +274,10 @@ if __name__ == "__main__":
help="The weight decay for the optimizer (default is Adam)",
)
parser.add_argument(
"--meta_batch", type=int, default=64, help="The batch size for the meta-model",
"--meta_batch",
type=int,
default=64,
help="The batch size for the meta-model",
)
parser.add_argument(
"--sampler_enlarge",
@ -284,7 +299,10 @@ if __name__ == "__main__":
"--workers", type=int, default=4, help="The number of workers in parallel."
)
parser.add_argument(
"--device", type=str, default="cpu", help="",
"--device",
type=str,
default="cpu",
help="",
)
# Random Seed
parser.add_argument("--rand_seed", type=int, default=-1, help="manual seed")

3
exps/LFNA/lfna_meta_model.py
View File

@ -75,7 +75,8 @@ class LFNA_Meta(super_core.SuperModule):
# unknown token
self.register_parameter(
"_unknown_token", torch.nn.Parameter(torch.Tensor(1, time_embedding)),
"_unknown_token",
torch.nn.Parameter(torch.Tensor(1, time_embedding)),
)
# initialization

6
exps/LFNA/vis-synthetic.py
View File

@ -164,8 +164,10 @@ def compare_cl(save_dir):
)
print("Save all figures into {:}".format(save_dir))
save_dir = save_dir.resolve()
base_cmd = "ffmpeg -y -i {xdir}/%04d.png -vf fps=1 -vf scale=2200:1800 -vb 5000k".format(
xdir=save_dir
base_cmd = (
"ffmpeg -y -i {xdir}/%04d.png -vf fps=1 -vf scale=2200:1800 -vb 5000k".format(
xdir=save_dir
)
)
video_cmd = "{:} -pix_fmt yuv420p {xdir}/compare-cl.mp4".format(
base_cmd, xdir=save_dir