Feature: Pytest Slow Mark

CONTRIBUTING.md

@@ -78,6 +78,13 @@ by [CI pipelines](#CI). Before pushing your changes to the remote we recommend
 to execute `pytest` locally in order to detect mistakes early on and to avoid
 failing pipelines.
 
+Slow tests (> 5s) are marked by the `@pytest.mark.slow` decorator.
+To run all tests except the slow ones, use:
+
+```shell
+pytest -m "not slow"
+```
+
 ## Notebooks
 
 We use notebooks both as documentation (copied over to `docs/examples`) and as

pyproject.toml

@@ -7,3 +7,8 @@ build-backend = "setuptools.build_meta"
 [tool.setuptools_scm]
 # See configuration details in https://github.com/pypa/setuptools_scm
 version_scheme = "no-guess-dev"
+
+[tool.pytest.ini_options]
+markers = [
+    "slow: marks tests as slow (> 5s)",
+]

tests/operators/test_deeponet.py

@@ -1,5 +1,6 @@
 import torch
 import matplotlib.pyplot as plt
+import pytest
 
 from continuity.plotting import plot, plot_evaluation
 from torch.utils.data import DataLoader
@@ -40,6 +41,7 @@ def test_output_shape():
     assert v_other_pred.shape == v_other.shape
 
 
+@pytest.mark.slow
 def test_deeponet():
     # Parameters
     num_sensors = 16

tests/operators/test_neuraloperator.py

@@ -1,3 +1,4 @@
+import pytest
 import torch
 import matplotlib.pyplot as plt
 from continuity.data import Sine
@@ -9,6 +10,7 @@
 torch.manual_seed(0)
 
 
+@pytest.mark.slow
 def test_neuraloperator():
     # Parameters
     num_sensors = 16

tests/test_optuna.py

@@ -1,3 +1,4 @@
+import pytest
 import torch
 from torch.utils.data import DataLoader
 from continuity.benchmarks.sine import SineBenchmark
@@ -10,6 +11,7 @@
 torch.manual_seed(0)
 
 
+@pytest.mark.slow
 def test_optuna():
     def objective(trial):
         trunk_width = trial.suggest_int("trunk_width", 4, 16)