bump: compatible with Lightning v2

CHANGELOG.md

@@ -15,6 +15,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 - Revision of the MoCo SSL model ([#928](https://github.com/PyTorchLightning/pytorch-lightning-bolts/pull/928))
 
+- Updated lightning dependency to support lightning 2.x ([#1094](https://github.com/Lightning-AI/pytorch-lightning/pull/2671))
+
 
 ### Deprecated
 

requirements/base.txt

@@ -1,6 +1,6 @@
 numpy <1.26.0
-pytorch-lightning >1.7.0, <2.0.0  # strict
-torchmetrics >=0.10.0, <0.12.0
+lightning >=2.0.0  # strict
+torchmetrics >=0.7.0, <1.3.0
 lightning-utilities >0.3.1  # this is needed for PL 1.7
-torchvision >=0.10.0  # todo: move to topic related extras
+torchvision >=0.15.0, <0.19.0  # todo: move to topic related extras
 tensorboard >=2.9.1, <2.14.0  # for `TensorBoardLogger`

requirements/models.txt

@@ -1,4 +1,4 @@
-torchvision >=0.10.0
+torchvision >=0.15.0, <0.19.0
 scikit-learn >=1.0.2
 Pillow >9.0.0
 gym[atari] >=0.17.2, <0.22.0  # strict

src/pl_bolts/callbacks/byol_updates.py

@@ -2,7 +2,7 @@
 from typing import Sequence, Union
 
 import torch.nn as nn
-from pytorch_lightning import Callback, LightningModule, Trainer
+from lightning import Callback, LightningModule, Trainer
 from torch import Tensor
 
 

src/pl_bolts/callbacks/data_monitor.py

@@ -2,10 +2,10 @@
 
 import numpy as np
 import torch
-from pytorch_lightning import Callback, LightningModule, Trainer
-from pytorch_lightning.loggers import TensorBoardLogger, WandbLogger
-from pytorch_lightning.utilities import rank_zero_warn
-from pytorch_lightning.utilities.apply_func import apply_to_collection
+from lightning import Callback, LightningModule, Trainer
+from lightning.fabric.utilities import rank_zero_warn
+from lightning.fabric.utilities.apply_func import apply_to_collection
+from lightning.pytorch.loggers import TensorBoardLogger, WandbLogger
 from torch import Tensor, nn
 from torch.nn import Module
 from torch.utils.hooks import RemovableHandle
@@ -16,9 +16,9 @@
 
 # Backward compatibility for Lightning Logger
 try:
-    from pytorch_lightning.loggers import Logger
+    from lightning.pytorch.loggers import Logger
 except ImportError:
-    from pytorch_lightning.loggers import LightningLoggerBase as Logger
+    from lightning.pytorch.loggers import LightningLoggerBase as Logger
 
 if _WANDB_AVAILABLE:
     import wandb
@@ -112,7 +112,7 @@ def _is_logger_available(self, logger: Logger) -> bool:
         if not isinstance(logger, self.supported_loggers):
             rank_zero_warn(
                 f"{self.__class__.__name__} does not support logging with {logger.__class__.__name__}."
-                f" Supported loggers are: {', '.join((str(x.__name__) for x in self.supported_loggers))}"
+                f" Supported loggers are: {', '.join(str(x.__name__) for x in self.supported_loggers)}"
             )
             available = False
         return available

src/pl_bolts/callbacks/knn_online.py

@@ -1,8 +1,8 @@
 from typing import Optional, Tuple, Union
 
 import torch
-from pytorch_lightning import Callback, LightningModule, Trainer
-from pytorch_lightning.accelerators import Accelerator
+from lightning import Callback, LightningModule, Trainer
+from lightning.pytorch.accelerators import Accelerator
 from torch import Tensor
 from torch.nn import functional as F  # noqa: N812
 

src/pl_bolts/callbacks/printing.py

@@ -2,9 +2,9 @@
 from itertools import zip_longest
 from typing import Any, Callable, Dict, List, Optional
 
-from pytorch_lightning import LightningModule, Trainer
-from pytorch_lightning.callbacks import Callback
-from pytorch_lightning.utilities import rank_zero_info
+from lightning import LightningModule, Trainer
+from lightning.fabric.utilities import rank_zero_info
+from lightning.pytorch.callbacks import Callback
 
 from pl_bolts.utils.stability import under_review
 

src/pl_bolts/callbacks/sparseml.py

@@ -14,10 +14,14 @@
 from typing import Any, Optional
 
 import torch
-from pytorch_lightning import Callback, LightningModule, Trainer
-from pytorch_lightning.utilities.exceptions import MisconfigurationException
+from lightning import Callback, LightningModule, Trainer
+from lightning.fabric.utilities.exceptions import MisconfigurationException
 
-from pl_bolts.utils import _SPARSEML_AVAILABLE, _SPARSEML_TORCH_SATISFIED, _SPARSEML_TORCH_SATISFIED_ERROR
+from pl_bolts.utils import (
+    _SPARSEML_AVAILABLE,
+    _SPARSEML_TORCH_SATISFIED,
+    _SPARSEML_TORCH_SATISFIED_ERROR,
+)
 
 if _SPARSEML_TORCH_SATISFIED:
     from sparseml.pytorch.optim import ScheduledModifierManager

src/pl_bolts/callbacks/ssl_online.py

@@ -2,8 +2,8 @@
 from typing import Any, Dict, Optional, Sequence, Tuple, Union
 
 import torch
-from pytorch_lightning import Callback, LightningModule, Trainer
-from pytorch_lightning.utilities import rank_zero_warn
+from lightning import Callback, LightningModule, Trainer
+from lightning.fabric.utilities import rank_zero_warn
 from torch import Tensor, nn
 from torch.nn import functional as F  # noqa: N812
 from torch.optim import Optimizer

src/pl_bolts/callbacks/torch_ort.py

@@ -11,8 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from pytorch_lightning import Callback, LightningModule, Trainer
-from pytorch_lightning.utilities.exceptions import MisconfigurationException
+from lightning import Callback, LightningModule, Trainer
+from lightning.fabric.utilities.exceptions import MisconfigurationException
 
 from pl_bolts.utils import _TORCH_ORT_AVAILABLE
 

src/pl_bolts/callbacks/variational.py

@@ -2,8 +2,8 @@
 
 import numpy as np
 import torch
-from pytorch_lightning import LightningModule, Trainer
-from pytorch_lightning.callbacks import Callback
+from lightning import LightningModule, Trainer
+from lightning.pytorch.callbacks import Callback
 from torch import Tensor
 
 from pl_bolts.utils import _TORCHVISION_AVAILABLE

src/pl_bolts/callbacks/verification/base.py

@@ -4,9 +4,9 @@
 from typing import Any, Optional
 
 import torch.nn as nn
-from pytorch_lightning import Callback, LightningModule
-from pytorch_lightning.utilities import move_data_to_device, rank_zero_warn
-from pytorch_lightning.utilities.signature_utils import is_param_in_hook_signature
+from lightning import Callback, LightningModule
+from lightning.fabric.utilities import move_data_to_device, rank_zero_warn
+from lightning.pytorch.utilities.signature_utils import is_param_in_hook_signature
 
 from pl_bolts.utils.stability import under_review
 

src/pl_bolts/callbacks/verification/batch_gradient.py

@@ -4,12 +4,15 @@
 
 import torch
 import torch.nn as nn
-from pytorch_lightning import LightningModule, Trainer
-from pytorch_lightning.utilities.apply_func import apply_to_collection
-from pytorch_lightning.utilities.exceptions import MisconfigurationException
+from lightning import LightningModule, Trainer
+from lightning.fabric.utilities.apply_func import apply_to_collection
+from lightning.fabric.utilities.exceptions import MisconfigurationException
 from torch import Tensor
 
-from pl_bolts.callbacks.verification.base import VerificationBase, VerificationCallbackBase
+from pl_bolts.callbacks.verification.base import (
+    VerificationBase,
+    VerificationCallbackBase,
+)
 from pl_bolts.utils.stability import under_review
 
 

src/pl_bolts/callbacks/vision/confused_logit.py

@@ -1,7 +1,7 @@
 from typing import Sequence
 
 import torch
-from pytorch_lightning import Callback, LightningModule, Trainer
+from lightning import Callback, LightningModule, Trainer
 from torch import Tensor, nn
 
 from pl_bolts.utils import _MATPLOTLIB_AVAILABLE

src/pl_bolts/callbacks/vision/image_generation.py

@@ -1,7 +1,7 @@
 from typing import Optional, Tuple
 
 import torch
-from pytorch_lightning import Callback, LightningModule, Trainer
+from lightning import Callback, LightningModule, Trainer
 
 from pl_bolts.utils import _TORCHVISION_AVAILABLE
 from pl_bolts.utils.stability import under_review

src/pl_bolts/callbacks/vision/sr_image_logger.py

@@ -3,7 +3,7 @@
 import pytorch_lightning as pl
 import torch
 import torch.nn.functional as F  # noqa: N812
-from pytorch_lightning import Callback
+from lightning import Callback
 
 from pl_bolts.utils import _TORCHVISION_AVAILABLE
 from pl_bolts.utils.stability import under_review

src/pl_bolts/datamodules/cityscapes_datamodule.py

@@ -1,6 +1,6 @@
 from typing import Any, Callable, Optional
 
-from pytorch_lightning import LightningDataModule
+from lightning import LightningDataModule
 from torch.utils.data import DataLoader
 
 from pl_bolts.utils import _TORCHVISION_AVAILABLE

src/pl_bolts/datamodules/imagenet_datamodule.py

@@ -2,7 +2,7 @@
 from argparse import ArgumentParser
 from typing import Any, Callable, Optional
 
-from pytorch_lightning import LightningDataModule
+from lightning import LightningDataModule
 from torch.utils.data import DataLoader
 
 from pl_bolts.datasets import UnlabeledImagenet

src/pl_bolts/datamodules/kitti_datamodule.py

@@ -2,7 +2,7 @@
 from typing import Any, Callable, Optional
 
 import torch
-from pytorch_lightning import LightningDataModule
+from lightning import LightningDataModule
 from torch.utils.data import DataLoader
 from torch.utils.data.dataset import random_split
 

src/pl_bolts/datamodules/sklearn_datamodule.py

@@ -2,7 +2,7 @@
 from typing import Any, Tuple
 
 import numpy as np
-from pytorch_lightning import LightningDataModule
+from lightning import LightningDataModule
 from torch.utils.data import DataLoader, Dataset
 
 from pl_bolts.utils import _SKLEARN_AVAILABLE

src/pl_bolts/datamodules/sr_datamodule.py

@@ -1,6 +1,6 @@
 from typing import Any
 
-from pytorch_lightning import LightningDataModule
+from lightning import LightningDataModule
 from torch.utils.data import DataLoader, Dataset
 
 from pl_bolts.utils.stability import under_review

src/pl_bolts/datamodules/ssl_imagenet_datamodule.py

@@ -1,7 +1,7 @@
 import os
 from typing import Any, Callable, Optional
 
-from pytorch_lightning import LightningDataModule
+from lightning import LightningDataModule
 from torch.utils.data import DataLoader
 
 from pl_bolts.datasets import UnlabeledImagenet

src/pl_bolts/datamodules/stl10_datamodule.py

@@ -3,7 +3,7 @@
 from typing import Any, Callable, Optional
 
 import torch
-from pytorch_lightning import LightningDataModule
+from lightning import LightningDataModule
 from torch.utils.data import DataLoader, random_split
 
 from pl_bolts.datasets import ConcatDataset

src/pl_bolts/datamodules/vision_datamodule.py

@@ -3,7 +3,7 @@
 from typing import Any, Callable, List, Optional, Union
 
 import torch
-from pytorch_lightning import LightningDataModule
+from lightning import LightningDataModule
 from torch.utils.data import DataLoader, Dataset, random_split
 
 

src/pl_bolts/datamodules/vocdetection_datamodule.py

@@ -2,7 +2,7 @@
 from typing import Any, Callable, Dict, List, Optional, Tuple
 
 import torch
-from pytorch_lightning import LightningDataModule
+from lightning import LightningDataModule
 from torch import Tensor
 from torch.utils.data import DataLoader, Dataset
 

src/pl_bolts/datasets/array_dataset.py

@@ -1,6 +1,6 @@
 from typing import Tuple, Union
 
-from pytorch_lightning.utilities import exceptions
+from lightning.fabric.utilities import exceptions
 from torch.utils.data import Dataset
 
 from pl_bolts.datasets.base_dataset import DataModel, TArrays

src/pl_bolts/losses/self_supervised_learning.py

@@ -307,7 +307,7 @@ def forward(self, anchor_maps, positive_maps):
         Example:
 
             >>> import torch
-            >>> from pytorch_lightning import seed_everything
+            >>> from lightning import seed_everything
             >>> seed_everything(0)
             0
             >>> a1 = torch.rand(3, 5, 2, 2)

src/pl_bolts/models/autoencoders/basic_ae/basic_ae_module.py

@@ -2,7 +2,7 @@
 from argparse import ArgumentParser
 
 import torch
-from pytorch_lightning import LightningModule, Trainer
+from lightning import LightningModule, Trainer
 from torch import nn
 from torch.nn import functional as F  # noqa: N812
 
@@ -154,7 +154,11 @@ def add_model_specific_args(parent_parser):
 
 @under_review()
 def cli_main(args=None):
-    from pl_bolts.datamodules import CIFAR10DataModule, ImagenetDataModule, STL10DataModule
+    from pl_bolts.datamodules import (
+        CIFAR10DataModule,
+        ImagenetDataModule,
+        STL10DataModule,
+    )
 
     parser = ArgumentParser()
     parser.add_argument("--dataset", default="cifar10", type=str, choices=["cifar10", "stl10", "imagenet"])

src/pl_bolts/models/autoencoders/basic_vae/basic_vae_module.py

@@ -2,7 +2,7 @@
 from argparse import ArgumentParser
 
 import torch
-from pytorch_lightning import LightningModule, Trainer, seed_everything
+from lightning import LightningModule, Trainer, seed_everything
 from torch import nn
 from torch.nn import functional as F  # noqa: N812
 
@@ -187,7 +187,11 @@ def add_model_specific_args(parent_parser):
 
 @under_review()
 def cli_main(args=None):
-    from pl_bolts.datamodules import CIFAR10DataModule, ImagenetDataModule, STL10DataModule
+    from pl_bolts.datamodules import (
+        CIFAR10DataModule,
+        ImagenetDataModule,
+        STL10DataModule,
+    )
 
     seed_everything()
 

src/pl_bolts/models/detection/faster_rcnn/faster_rcnn_module.py

@@ -2,16 +2,21 @@
 from typing import Any, Optional, Union
 
 import torch
-from pytorch_lightning import LightningModule, Trainer, seed_everything
+from lightning import LightningModule, Trainer, seed_everything
 
 from pl_bolts.models.detection.faster_rcnn import create_fasterrcnn_backbone
 from pl_bolts.utils import _TORCHVISION_AVAILABLE
 from pl_bolts.utils.stability import under_review
 from pl_bolts.utils.warnings import warn_missing_pkg
 
 if _TORCHVISION_AVAILABLE:
-    from torchvision.models.detection.faster_rcnn import FasterRCNN as torchvision_FasterRCNN
-    from torchvision.models.detection.faster_rcnn import FastRCNNPredictor, fasterrcnn_resnet50_fpn
+    from torchvision.models.detection.faster_rcnn import (
+        FasterRCNN as torchvision_FasterRCNN,
+    )
+    from torchvision.models.detection.faster_rcnn import (
+        FastRCNNPredictor,
+        fasterrcnn_resnet50_fpn,
+    )
     from torchvision.ops import box_iou
 else:  # pragma: no cover
     warn_missing_pkg("torchvision")