fix: remove removed CLI syntax from examples

examples/cbc_iris.py

@@ -5,8 +5,8 @@ import warnings
 
 import prototorch as pt
 import pytorch_lightning as pl
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import CBC, VisCBC2D
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader
 
@@ -19,7 +19,8 @@ if __name__ == "__main__":
 
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Dataset
@@ -53,8 +54,10 @@ if __name__ == "__main__":
     )
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
         ],

examples/dynamic_pruning.py

@@ -7,13 +7,13 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import (
     CELVQ,
     PruneLoserPrototypes,
     VisGLVQ2D,
 )
 from pytorch_lightning.callbacks import EarlyStopping
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader
 
@@ -26,7 +26,8 @@ if __name__ == "__main__":
 
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Dataset
@@ -83,8 +84,10 @@ if __name__ == "__main__":
     )
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
             pruning,

examples/glvq_iris.py

@@ -7,8 +7,8 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import GLVQ, VisGLVQ2D
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.optim.lr_scheduler import ExponentialLR
 from torch.utils.data import DataLoader
@@ -21,7 +21,8 @@ if __name__ == "__main__":
     seed_everything(seed=4)
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Dataset
@@ -55,8 +56,10 @@ if __name__ == "__main__":
     vis = VisGLVQ2D(data=train_ds)
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
         ],

examples/gmlvq_iris.py

@@ -6,8 +6,8 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import GMLVQ, VisGMLVQ2D
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.optim.lr_scheduler import ExponentialLR
 from torch.utils.data import DataLoader
@@ -22,7 +22,8 @@ if __name__ == "__main__":
 
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Dataset
@@ -59,8 +60,10 @@ if __name__ == "__main__":
     vis = VisGMLVQ2D(data=train_ds)
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
         ],

examples/gmlvq_mnist.py

@@ -6,13 +6,13 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import (
     ImageGMLVQ,
     PruneLoserPrototypes,
     VisImgComp,
 )
 from pytorch_lightning.callbacks import EarlyStopping
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader
 from torchvision import transforms
@@ -26,7 +26,8 @@ if __name__ == "__main__":
     seed_everything(seed=4)
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Dataset
@@ -96,8 +97,10 @@ if __name__ == "__main__":
     )
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
             pruning,

examples/gmlvq_spiral.py

@@ -6,13 +6,13 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import (
     GMLVQ,
     PruneLoserPrototypes,
     VisGLVQ2D,
 )
 from pytorch_lightning.callbacks import EarlyStopping
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader
 
@@ -25,7 +25,8 @@ if __name__ == "__main__":
 
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Dataset
@@ -78,8 +79,10 @@ if __name__ == "__main__":
     )
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
             es,

examples/gng_iris.py

@@ -7,8 +7,8 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import GrowingNeuralGas, VisNG2D
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader
 
@@ -18,7 +18,8 @@ warnings.filterwarnings("ignore", category=UserWarning)
 if __name__ == "__main__":
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Reproducibility
@@ -51,8 +52,10 @@ if __name__ == "__main__":
     vis = VisNG2D(data=train_loader)
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
         ],

examples/grlvq_iris.py

@@ -6,8 +6,8 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import GRLVQ, VisSiameseGLVQ2D
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.optim.lr_scheduler import ExponentialLR
 from torch.utils.data import DataLoader
@@ -22,7 +22,8 @@ if __name__ == "__main__":
 
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Dataset
@@ -58,8 +59,10 @@ if __name__ == "__main__":
     vis = VisSiameseGLVQ2D(data=train_ds)
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
         ],

examples/gtlvq_mnist.py

@@ -6,13 +6,13 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import (
     ImageGTLVQ,
     PruneLoserPrototypes,
     VisImgComp,
 )
 from pytorch_lightning.callbacks import EarlyStopping
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader
 from torchvision import transforms
@@ -27,7 +27,8 @@ if __name__ == "__main__":
 
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Dataset
@@ -100,8 +101,10 @@ if __name__ == "__main__":
 
     # Setup trainer
     # using GPUs here is strongly recommended!
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
             pruning,

examples/gtlvq_moons.py

@@ -7,9 +7,9 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import GTLVQ, VisGLVQ2D
 from pytorch_lightning.callbacks import EarlyStopping
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader
 
@@ -19,7 +19,8 @@ warnings.filterwarnings("ignore", category=UserWarning)
 if __name__ == "__main__":
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Reproducibility
@@ -61,8 +62,10 @@ if __name__ == "__main__":
     )
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
             es,

examples/knn_iris.py

@@ -18,7 +18,8 @@ warnings.filterwarnings("ignore", category=PossibleUserWarning)
 if __name__ == "__main__":
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Dataset
@@ -59,8 +60,10 @@ if __name__ == "__main__":
     )
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         max_epochs=1,
         callbacks=[
             vis,

examples/ksom_colors.py

@@ -7,10 +7,10 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from matplotlib import pyplot as plt
 from prototorch.models import KohonenSOM
 from prototorch.utils.colors import hex_to_rgb
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader, TensorDataset
 
@@ -58,7 +58,8 @@ class Vis2DColorSOM(pl.Callback):
 if __name__ == "__main__":
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Reproducibility
@@ -104,8 +105,10 @@ if __name__ == "__main__":
     vis = Vis2DColorSOM(data=data)
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         max_epochs=500,
         callbacks=[
             vis,

examples/lgmlvq_moons.py

@@ -7,9 +7,9 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import LGMLVQ, VisGLVQ2D
 from pytorch_lightning.callbacks import EarlyStopping
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader
 
@@ -19,7 +19,8 @@ warnings.filterwarnings("ignore", category=UserWarning)
 if __name__ == "__main__":
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Reproducibility
@@ -62,8 +63,10 @@ if __name__ == "__main__":
     )
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
             es,

examples/lvqmln_iris.py

@@ -6,12 +6,12 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import (
     LVQMLN,
     PruneLoserPrototypes,
     VisSiameseGLVQ2D,
 )
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader
 
@@ -39,7 +39,8 @@ class Backbone(torch.nn.Module):
 if __name__ == "__main__":
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Dataset
@@ -88,8 +89,10 @@ if __name__ == "__main__":
     )
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
             pruning,

examples/median_lvq_iris.py

@@ -6,9 +6,9 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import MedianLVQ, VisGLVQ2D
 from pytorch_lightning.callbacks import EarlyStopping
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader
 
@@ -20,7 +20,8 @@ if __name__ == "__main__":
     seed_everything(seed=4)
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Dataset
@@ -53,8 +54,10 @@ if __name__ == "__main__":
     )
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
             es,

examples/ng_iris.py

@@ -6,8 +6,8 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import NeuralGas, VisNG2D
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from sklearn.datasets import load_iris
 from sklearn.preprocessing import StandardScaler
@@ -23,7 +23,8 @@ if __name__ == "__main__":
 
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Prepare and pre-process the dataset
@@ -60,8 +61,10 @@ if __name__ == "__main__":
     vis = VisNG2D(data=train_ds)
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
         ],

examples/rslvq_iris.py

@@ -6,8 +6,8 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import RSLVQ, VisGLVQ2D
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader
 
@@ -17,7 +17,8 @@ warnings.filterwarnings("ignore", category=UserWarning)
 if __name__ == "__main__":
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Reproducibility
@@ -54,8 +55,10 @@ if __name__ == "__main__":
     vis = VisGLVQ2D(data=train_ds)
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
         ],

examples/siamese_glvq_iris.py

@@ -6,8 +6,8 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import SiameseGLVQ, VisSiameseGLVQ2D
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader
 
@@ -35,7 +35,8 @@ class Backbone(torch.nn.Module):
 if __name__ == "__main__":
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Dataset
@@ -69,8 +70,10 @@ if __name__ == "__main__":
     vis = VisSiameseGLVQ2D(data=train_ds, border=0.1)
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
         ],

examples/siamese_gtlvq_iris.py

@@ -6,8 +6,8 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import SiameseGTLVQ, VisSiameseGLVQ2D
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.utils.data import DataLoader
 
@@ -35,7 +35,8 @@ class Backbone(torch.nn.Module):
 if __name__ == "__main__":
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Dataset
@@ -71,8 +72,10 @@ if __name__ == "__main__":
     vis = VisSiameseGLVQ2D(data=train_ds, border=0.1)
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
         ],

examples/warm_starting.py

@@ -6,6 +6,7 @@ import warnings
 import prototorch as pt
 import pytorch_lightning as pl
 import torch
+from lightning_fabric.utilities.seed import seed_everything
 from prototorch.models import (
     GLVQ,
     KNN,
@@ -14,7 +15,6 @@ from prototorch.models import (
     VisGLVQ2D,
 )
 from pytorch_lightning.callbacks import EarlyStopping
-from pytorch_lightning.utilities.seed import seed_everything
 from pytorch_lightning.utilities.warnings import PossibleUserWarning
 from torch.optim.lr_scheduler import ExponentialLR
 from torch.utils.data import DataLoader
@@ -27,7 +27,8 @@ if __name__ == "__main__":
     seed_everything(seed=4)
     # Command-line arguments
     parser = argparse.ArgumentParser()
-    parser = pl.Trainer.add_argparse_args(parser)
+    parser.add_argument("--gpus", type=int, default=0)
+    parser.add_argument("--fast_dev_run", type=bool, default=False)
     args = parser.parse_args()
 
     # Prepare the data
@@ -108,8 +109,10 @@ if __name__ == "__main__":
     )
 
     # Setup trainer
-    trainer = pl.Trainer.from_argparse_args(
-        args,
+    trainer = pl.Trainer(
+        accelerator="cuda" if args.gpus else "cpu",
+        devices=args.gpus if args.gpus else "auto",
+        fast_dev_run=args.fast_dev_run,
         callbacks=[
             vis,
             pruning,

setup.py

@@ -22,10 +22,10 @@ with open("README.md") as fh:
     long_description = fh.read()
 
 INSTALL_REQUIRES = [
-    "prototorch>=0.7.3",
-    "pytorch_lightning>=1.6.0",
-    "torchmetrics<0.10.0",
-    "protobuf<3.20.0",
+    "prototorch>=0.7.5",
+    "lightning>=2.0.0",
+    "torchmetrics",
+    "protobuf",
 ]
 CLI = [
     "jsonargparse",
@@ -65,7 +65,7 @@ setup(
     url=PROJECT_URL,
     download_url=DOWNLOAD_URL,
     license="MIT",
-    python_requires=">=3.7",
+    python_requires=">=3.8",
     install_requires=INSTALL_REQUIRES,
     extras_require={
         "dev": DEV,
@@ -82,10 +82,10 @@ setup(
         "License :: OSI Approved :: MIT License",
         "Natural Language :: English",
         "Programming Language :: Python :: 3",
+        "Programming Language :: Python :: 3.11",
         "Programming Language :: Python :: 3.10",
         "Programming Language :: Python :: 3.9",
         "Programming Language :: Python :: 3.8",
-        "Programming Language :: Python :: 3.7",
         "Operating System :: OS Independent",
         "Topic :: Scientific/Engineering :: Artificial Intelligence",
         "Topic :: Software Development :: Libraries",