update project (#82)

* update
* prune
* ruff
* fixed
* <2.4

---------

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

.github/workflows/ci_install-pkg.yml

@@ -16,6 +16,6 @@ jobs:
       import-name: "quick_start"
       testing-matrix: |
         {
-          "os": ["ubuntu-20.04", "macos-11", "windows-2022"],
-          "python-version": ["3.8"]
+          "os": ["ubuntu-22.04", "macos-13", "windows-2022"],
+          "python-version": ["3.10"]
         }

.github/workflows/ci_testing.yml

@@ -11,14 +11,14 @@ concurrency:
 
 jobs:
   pytest:
-    runs-on: ubuntu-20.04
+    runs-on: ubuntu-22.04
     timeout-minutes: 10
     steps:
       - uses: actions/checkout@v4
-      - name: Set up Python 3.8
+      - name: Set up Python 3.10
         uses: actions/setup-python@v5
         with:
-          python-version: "3.8"
+          python-version: "3.10"
 
       - uses: actions/cache@v4
         with:
@@ -27,13 +27,11 @@ jobs:
           restore-keys: |
             ${{ runner.os }}-pip-
 
-      - name: Install Lightning
+      - name: Install packages
         run: |
-          pip install -U lightning -r requirements.txt -r tests/requirements.txt \
+          pip install -U -r requirements.txt -r tests/requirements.txt \
             -f https://download.pytorch.org/whl/cpu/torch_stable.html
           pip list
-          lightning --version
 
       - name: Tests
-        run: |
-          python -m pytest tests
+        run: python -m pytest tests

.pre-commit-config.yaml

@@ -1,5 +1,5 @@
 default_language_version:
-  python: python3.8
+  python: python3
 
 ci:
   autofix_prs: true
@@ -21,19 +21,6 @@ repos:
       - id: check-docstring-first
       - id: detect-private-key
 
-  - repo: https://github.com/asottile/pyupgrade
-    rev: v3.17.0
-    hooks:
-      - id: pyupgrade
-        args: [--py38-plus]
-        name: Upgrade code
-
-  - repo: https://github.com/psf/black
-    rev: 24.4.2
-    hooks:
-      - id: black
-        name: Black code
-
   - repo: https://github.com/executablebooks/mdformat
     rev: 0.7.17
     hooks:
@@ -43,15 +30,10 @@ repos:
           - mdformat-black
           - mdformat_frontmatter
 
-  - repo: https://github.com/asottile/yesqa
-    rev: v1.5.0
-    hooks:
-      - id: yesqa
-
-  - repo: https://github.com/PyCQA/flake8
-    rev: 7.1.0
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.5.5
     hooks:
-      - id: flake8
-        args:
-          - "--max-line-length=120"
-          - "--ignore=E266"
+      - id: ruff
+        args: ["--fix", "--line-length=120", "--target-version=py39"]
+      - id: ruff-format
+        args: ["--line-length=120"]

quick_start/components.py

@@ -58,9 +58,7 @@ def trainer_pre_fn(self, *args, work=None, **kwargs):
             return {}, args, kwargs
 
         # 5. Patch the `__init__` method of the Trainer to inject our callback with a reference to the work.
-        tracer.add_traced(
-            Trainer, "__init__", pre_fn=partial(trainer_pre_fn, work=self)
-        )
+        tracer.add_traced(Trainer, "__init__", pre_fn=partial(trainer_pre_fn, work=self))
         return tracer
 
     def run(self, *args, **kwargs):
@@ -96,9 +94,7 @@ def on_after_run(self, script_globals):
         lightning_module = script_globals["cli"].trainer.lightning_module
 
         # 2. From the checkpoint_callback, we are accessing the best model weights
-        checkpoint = torch.load(
-            script_globals["cli"].trainer.checkpoint_callback.best_model_path
-        )
+        checkpoint = torch.load(script_globals["cli"].trainer.checkpoint_callback.best_model_path)
 
         # 3. Load the best weights and torchscript the model.
         lightning_module.load_state_dict(checkpoint["state_dict"])
@@ -110,9 +106,7 @@ def on_after_run(self, script_globals):
         self.best_model_path = Path("model_weight.pt")
 
         # 5. Keep track of the metrics.
-        self.best_model_score = float(
-            script_globals["cli"].trainer.checkpoint_callback.best_model_score
-        )
+        self.best_model_score = float(script_globals["cli"].trainer.checkpoint_callback.best_model_score)
 
 
 class ImageServeGradio(ServeGradio):

quick_start/setup_tools.py

@@ -19,9 +19,7 @@
 _PROJECT_ROOT = os.path.dirname(os.path.dirname(__file__))
 
 
-def _load_requirements(
-    path_dir: str, file_name: str = "requirements.txt", comment_char: str = "#"
-) -> List[str]:
+def _load_requirements(path_dir: str, file_name: str = "requirements.txt", comment_char: str = "#") -> List[str]:
     """Load requirements from a file.
 
     >>> _load_requirements(_PROJECT_ROOT)  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
@@ -62,13 +60,9 @@ def _load_readme_description(path_dir: str, homepage: str, ver: str) -> str:
 
     # readthedocs badge
     text = text.replace("badge/?version=stable", f"badge/?version={ver}")
-    text = text.replace(
-        "lightning.readthedocs.io/en/stable/", f"lightning.readthedocs.io/en/{ver}"
-    )
+    text = text.replace("lightning.readthedocs.io/en/stable/", f"lightning.readthedocs.io/en/{ver}")
     # codecov badge
-    text = text.replace(
-        "/branch/master/graph/badge.svg", f"/release/{ver}/graph/badge.svg"
-    )
+    text = text.replace("/branch/master/graph/badge.svg", f"/release/{ver}/graph/badge.svg")
     # replace github badges for release ones
     text = text.replace("badge.svg?branch=master&event=push", f"badge.svg?tag={ver}")
 

requirements.txt

@@ -5,5 +5,5 @@ gradio <=3.45.2
 pyyaml <=6.0.1
 protobuf >4.21, <5.28.0  # 4.21 breaks with wandb, tensorboard, or pytorch-lightning: https://github.com/protocolbuffers/protobuf/issues/10048
 websockets
-lightning[app] >=2.1.0
+lightning[app] >=2.1.0, <2.4.0
 tensorboard

setup.py

@@ -10,19 +10,15 @@
 
 
 def _load_py_module(fname, pkg=PACKAGE_NAME):
-    spec = spec_from_file_location(
-        os.path.join(pkg, fname), os.path.join(_PATH_ROOT, pkg, fname)
-    )
+    spec = spec_from_file_location(os.path.join(pkg, fname), os.path.join(_PATH_ROOT, pkg, fname))
     py = module_from_spec(spec)
     spec.loader.exec_module(py)
     return py
 
 
 about = _load_py_module("__about__.py")
 setup_tools = _load_py_module("setup_tools.py")
-long_description = setup_tools._load_readme_description(
-    _PATH_ROOT, homepage=about.__homepage__, ver=about.__version__
-)
+long_description = setup_tools._load_readme_description(_PATH_ROOT, homepage=about.__homepage__, ver=about.__version__)
 
 # https://packaging.python.org/discussions/install-requires-vs-requirements /
 # keep the meta-data here for simplicity in reading this file... it's not obvious

train_script.py

@@ -82,20 +82,12 @@ def prepare_data(self) -> None:
         MNIST("./data", download=True)
 
     def train_dataloader(self):
-        train_dataset = MNIST(
-            "./data", train=True, download=False, transform=self.transform
-        )
-        return torch.utils.data.DataLoader(
-            train_dataset, batch_size=self.hparams.batch_size
-        )
+        train_dataset = MNIST("./data", train=True, download=False, transform=self.transform)
+        return torch.utils.data.DataLoader(train_dataset, batch_size=self.hparams.batch_size)
 
     def val_dataloader(self):
-        val_dataset = MNIST(
-            "./data", train=False, download=False, transform=self.transform
-        )
-        return torch.utils.data.DataLoader(
-            val_dataset, batch_size=self.hparams.batch_size
-        )
+        val_dataset = MNIST("./data", train=False, download=False, transform=self.transform)
+        return torch.utils.data.DataLoader(val_dataset, batch_size=self.hparams.batch_size)
 
 
 if __name__ == "__main__":