Update to pytorch lightning 2.0.2, remove lightning bolts dependency and other fixes (#344)

* updated lightning version, removed bolts dependency, fixed umap, updated some python syntax

* remove support for 3.7 and fixed timm import

* fixes

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Update dali_tests.yml

* Update sphinx-linkcheck.yml

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: vturrisi

.github/workflows/dali_tests.yml

@@ -12,7 +12,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python: [3.7, 3.8, 3.9]
+        python: [3.8, 3.9]
         os: [ubuntu-latest]
 
     steps:

.github/workflows/sphinx-linkcheck.yml

@@ -13,10 +13,10 @@ jobs:
     steps:
       - uses: actions/checkout@v2
 
-      - name: Set up Python 3.7
+      - name: Set up Python 3.9
         uses: actions/setup-python@v1
         with:
-          python-version: 3.7
+          python-version: 3.9
 
       - name: python dependencies
         run: |

.github/workflows/tests.yml

@@ -12,7 +12,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python: [3.7, 3.8, 3.9]
+        python: [3.8, 3.9]
         os: [ubuntu-latest, windows-latest]
 
     steps:

docs/source/conf.py

@@ -52,7 +52,7 @@
 def package_list_from_file(file):
     """List up package name (not containing version and extras) from a package list file"""
     mocked_packages = []
-    with open(file, "r") as fp:
+    with open(file) as fp:
         for ln in fp.readlines():
             # Example: `tqdm>=4.41.0` => `tqdm`
             # `[` is for package with extras

docs/source/solo/methods/base.rst

@@ -21,6 +21,8 @@
 import os
 from pathlib import Path
 
+from omegaconf import OmegaConf
+
 from solo.args.umap import parse_args_umap
 from solo.data.classification_dataloader import prepare_data
 from solo.methods import METHODS
@@ -38,15 +40,14 @@ def main():
     # load arguments
     with open(args_path) as f:
         method_args = json.load(f)
+    cfg = OmegaConf.create(method_args)
 
     # build the model
     model = (
         METHODS[method_args["method"]]
-        .load_from_checkpoint(ckpt_path, strict=False, **method_args)
+        .load_from_checkpoint(ckpt_path, strict=False, cfg=cfg)
         .backbone
     )
-    model.cuda()
-
     # prepare data
     train_loader, val_loader = prepare_data(
         args.dataset,
@@ -55,7 +56,7 @@ def main():
         data_format=args.data_format,
         batch_size=args.batch_size,
         num_workers=args.num_workers,
-        auto_augment=args.auto_augment,
+        auto_augment=False,
     )
 
     umap = OfflineUMAP()

docs/source/solo/methods/linear.rst

@@ -1,9 +1,8 @@
 torch>=1.10.0
 torchvision>=0.11.1
 einops
-pytorch-lightning>=1.7.0, <1.9.0
+pytorch-lightning==2.0.2
 torchmetrics>=0.6.0, <0.12.0
-lightning-bolts>=0.6.0
 tqdm
 wandb
 scipy

main_umap.py

@@ -49,4 +49,4 @@ devices: [0, 1, 2, 3, 4, 5, 6, 7]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

requirements.txt

@@ -49,4 +49,4 @@ devices: [0, 1, 2, 3, 4, 5, 6, 7]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/finetune/imagenet-100/mae.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/finetune/imagenet/mae.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/barlow.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/byol.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/deepclusterv2.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/dino.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/mocov2plus.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/mocov3.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/mocov3_vit.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/nnclr.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/ressl.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/simclr.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/simsiam.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/swav.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/vibcreg.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet-100/vicreg.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet/barlow.yaml

@@ -42,4 +42,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet/byol.yaml

@@ -55,4 +55,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/linear/imagenet/mocov2plus.yaml

@@ -50,4 +50,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar-multicrop/swav.yaml

@@ -53,4 +53,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/barlow.yaml

@@ -53,4 +53,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/byol.yaml

@@ -53,4 +53,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/deepclusterv2.yaml

@@ -53,4 +53,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/dino.yaml

@@ -50,4 +50,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/mae.yaml

@@ -54,4 +54,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/mocov2plus.yaml

@@ -54,4 +54,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/mocov3.yaml

@@ -52,4 +52,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/nnbyol.yaml

@@ -50,4 +50,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/nnclr.yaml

@@ -53,4 +53,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/nnsiam.yaml

@@ -50,4 +50,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/ressl.yaml

@@ -47,4 +47,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/simclr.yaml

@@ -46,4 +46,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/simsiam.yaml

@@ -54,4 +54,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/supcon.yaml

@@ -74,4 +74,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/swav.yaml

@@ -80,4 +80,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/vibcreg.yaml

@@ -70,4 +70,4 @@ devices: [0]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/vicreg.yaml

@@ -60,4 +60,4 @@ devices: [0, 1]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/cifar/wmse.yaml

@@ -53,4 +53,4 @@ devices: [0, 1]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/custom/byol.yaml

@@ -50,4 +50,4 @@ devices: [0, 1]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/imagenet-100-multicrop/byol.yaml

@@ -46,4 +46,4 @@ devices: [0, 1]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/imagenet-100-multicrop/simclr.yaml

@@ -50,4 +50,4 @@ devices: [0, 1]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/imagenet-100-multicrop/supcon.yaml

@@ -53,4 +53,4 @@ devices: [0, 1]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/imagenet-100/barlow.yaml

@@ -55,4 +55,4 @@ devices: [0, 1]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed

scripts/pretrain/imagenet-100/byol.yaml

@@ -54,4 +54,4 @@ devices: [0, 1]
 sync_batchnorm: True
 accelerator: "gpu"
 strategy: "ddp"
-precision: 16
+precision: 16-mixed