fix(tests): update tests after torch 2.4.1 (#20302)

* update

* test_loggers_pickle_all

* more...

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

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

* fix

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
(cherry picked from commit d1ca3c6)

pyproject.toml

@@ -76,7 +76,6 @@ ignore = [
  "S108",
  "E203", # conflicts with black
 ]
-ignore-init-module-imports = true
 
 [tool.ruff.lint.per-file-ignores]
 ".actions/*" = ["S101", "S310"]

requirements/typing.txt

@@ -1,5 +1,5 @@
 mypy==1.11.0
-torch==2.4.0
+torch==2.4.1
 
 types-Markdown
 types-PyYAML

src/lightning/fabric/utilities/imports.py

@@ -31,7 +31,9 @@
 
 _TORCH_GREATER_EQUAL_2_2 = compare_version("torch", operator.ge, "2.2.0")
 _TORCH_GREATER_EQUAL_2_3 = compare_version("torch", operator.ge, "2.3.0")
+_TORCH_EQUAL_2_4_0 = compare_version("torch", operator.eq, "2.4.0")
 _TORCH_GREATER_EQUAL_2_4 = compare_version("torch", operator.ge, "2.4.0")
+_TORCH_GREATER_EQUAL_2_4_1 = compare_version("torch", operator.ge, "2.4.1")
 
 _PYTHON_GREATER_EQUAL_3_10_0 = (sys.version_info.major, sys.version_info.minor) >= (3, 10)
 

tests/tests_pytorch/callbacks/test_early_stopping.py

@@ -23,7 +23,7 @@
 import cloudpickle
 import pytest
 import torch
-from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_4
+from lightning.fabric.utilities.imports import _TORCH_EQUAL_2_4_0
 from lightning.pytorch import Trainer, seed_everything
 from lightning.pytorch.callbacks import EarlyStopping, ModelCheckpoint
 from lightning.pytorch.demos.boring_classes import BoringModel
@@ -193,12 +193,12 @@ def test_pickling():
  early_stopping = EarlyStopping(monitor="foo")
 
  early_stopping_pickled = pickle.dumps(early_stopping)
- with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_GREATER_EQUAL_2_4 else nullcontext():
+ with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_EQUAL_2_4_0 else nullcontext():
  early_stopping_loaded = pickle.loads(early_stopping_pickled)
  assert vars(early_stopping) == vars(early_stopping_loaded)
 
  early_stopping_pickled = cloudpickle.dumps(early_stopping)
- with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_GREATER_EQUAL_2_4 else nullcontext():
+ with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_EQUAL_2_4_0 else nullcontext():
  early_stopping_loaded = cloudpickle.loads(early_stopping_pickled)
  assert vars(early_stopping) == vars(early_stopping_loaded)
 

tests/tests_pytorch/checkpointing/test_model_checkpoint.py

@@ -32,7 +32,7 @@
 import yaml
 from jsonargparse import ArgumentParser
 from lightning.fabric.utilities.cloud_io import _load as pl_load
-from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_4
+from lightning.fabric.utilities.imports import _TORCH_EQUAL_2_4_0
 from lightning.pytorch import Trainer, seed_everything
 from lightning.pytorch.callbacks import ModelCheckpoint
 from lightning.pytorch.demos.boring_classes import BoringModel
@@ -352,12 +352,12 @@ def test_pickling(tmp_path):
  ckpt = ModelCheckpoint(dirpath=tmp_path)
 
  ckpt_pickled = pickle.dumps(ckpt)
- with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_GREATER_EQUAL_2_4 else nullcontext():
+ with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_EQUAL_2_4_0 else nullcontext():
  ckpt_loaded = pickle.loads(ckpt_pickled)
  assert vars(ckpt) == vars(ckpt_loaded)
 
  ckpt_pickled = cloudpickle.dumps(ckpt)
- with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_GREATER_EQUAL_2_4 else nullcontext():
+ with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_EQUAL_2_4_0 else nullcontext():
  ckpt_loaded = cloudpickle.loads(ckpt_pickled)
  assert vars(ckpt) == vars(ckpt_loaded)
 

tests/tests_pytorch/core/test_metric_result_integration.py

@@ -19,7 +19,7 @@
 import lightning.pytorch as pl
 import pytest
 import torch
-from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_4
+from lightning.fabric.utilities.imports import _TORCH_EQUAL_2_4_0
 from lightning.fabric.utilities.warnings import PossibleUserWarning
 from lightning.pytorch import Trainer
 from lightning.pytorch.callbacks import OnExceptionCheckpoint
@@ -254,7 +254,7 @@ def lightning_log(fx, *args, **kwargs):
  }
 
  # make sure can be pickled
- with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_GREATER_EQUAL_2_4 else nullcontext():
+ with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_EQUAL_2_4_0 else nullcontext():
  pickle.loads(pickle.dumps(result))
  # make sure can be torch.loaded
  filepath = str(tmp_path / "result")

tests/tests_pytorch/helpers/test_datasets.py

@@ -17,7 +17,7 @@
 import cloudpickle
 import pytest
 import torch
-from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_4
+from lightning.fabric.utilities.imports import _TORCH_EQUAL_2_4_0
 
 from tests_pytorch import _PATH_DATASETS
 from tests_pytorch.helpers.datasets import MNIST, AverageDataset, TrialMNIST
@@ -44,9 +44,9 @@ def test_pickling_dataset_mnist(dataset_cls, args):
  mnist = dataset_cls(**args)
 
  mnist_pickled = pickle.dumps(mnist)
- with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_GREATER_EQUAL_2_4 else nullcontext():
+ with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_EQUAL_2_4_0 else nullcontext():
  pickle.loads(mnist_pickled)
 
  mnist_pickled = cloudpickle.dumps(mnist)
- with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_GREATER_EQUAL_2_4 else nullcontext():
+ with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_EQUAL_2_4_0 else nullcontext():
  cloudpickle.loads(mnist_pickled)

tests/tests_pytorch/loggers/test_all.py

@@ -20,7 +20,7 @@
 
 import pytest
 import torch
-from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_4
+from lightning.fabric.utilities.imports import _TORCH_EQUAL_2_4_0, _TORCH_GREATER_EQUAL_2_4_1
 from lightning.pytorch import Callback, Trainer
 from lightning.pytorch.demos.boring_classes import BoringModel
 from lightning.pytorch.loggers import (
@@ -163,7 +163,7 @@ def test_loggers_pickle_all(tmp_path, monkeypatch, logger_class):
  pytest.xfail(f"pickle test requires {logger_class.__class__} dependencies to be installed.")
 
 
-def _test_loggers_pickle(tmp_path, monkeypatch, logger_class):
+def _test_loggers_pickle(tmp_path, monkeypatch, logger_class: Logger):
  """Verify that pickling trainer with logger works."""
  _patch_comet_atexit(monkeypatch)
 
@@ -184,7 +184,11 @@ def _test_loggers_pickle(tmp_path, monkeypatch, logger_class):
  trainer = Trainer(max_epochs=1, logger=logger)
  pkl_bytes = pickle.dumps(trainer)
 
- with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_GREATER_EQUAL_2_4 else nullcontext():
+ with (
+ pytest.warns(FutureWarning, match="`weights_only=False`")
+ if _TORCH_EQUAL_2_4_0 or (_TORCH_GREATER_EQUAL_2_4_1 and logger_class not in (CSVLogger, TensorBoardLogger))
+ else nullcontext()
+ ):
  trainer2 = pickle.loads(pkl_bytes)
  trainer2.logger.log_metrics({"acc": 1.0})
 

tests/tests_pytorch/loggers/test_logger.py

@@ -21,7 +21,7 @@
 import numpy as np
 import pytest
 import torch
-from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_4
+from lightning.fabric.utilities.imports import _TORCH_EQUAL_2_4_0
 from lightning.fabric.utilities.logger import _convert_params, _sanitize_params
 from lightning.pytorch import Trainer
 from lightning.pytorch.demos.boring_classes import BoringDataModule, BoringModel
@@ -124,7 +124,7 @@ def test_multiple_loggers_pickle(tmp_path):
 
  trainer = Trainer(logger=[logger1, logger2])
  pkl_bytes = pickle.dumps(trainer)
- with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_GREATER_EQUAL_2_4 else nullcontext():
+ with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_EQUAL_2_4_0 else nullcontext():
  trainer2 = pickle.loads(pkl_bytes)
  for logger in trainer2.loggers:
  logger.log_metrics({"acc": 1.0}, 0)

tests/tests_pytorch/loggers/test_wandb.py

@@ -19,7 +19,7 @@
 
 import pytest
 import yaml
-from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_4
+from lightning.fabric.utilities.imports import _TORCH_EQUAL_2_4_0
 from lightning.pytorch import Trainer
 from lightning.pytorch.callbacks import ModelCheckpoint
 from lightning.pytorch.cli import LightningCLI
@@ -162,7 +162,7 @@ def name(self):
  assert trainer.logger.experiment, "missing experiment"
  assert trainer.log_dir == logger.save_dir
  pkl_bytes = pickle.dumps(trainer)
- with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_GREATER_EQUAL_2_4 else nullcontext():
+ with pytest.warns(FutureWarning, match="`weights_only=False`") if _TORCH_EQUAL_2_4_0 else nullcontext():
  trainer2 = pickle.loads(pkl_bytes)
 
  assert os.environ["WANDB_MODE"] == "dryrun"