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feat: Allow for disabling backend when running tests via pytest #2340

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merged 5 commits into from
Oct 9, 2023
Merged

feat: Allow for disabling backend when running tests via pytest #2340

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7286340
add a --disable-backend option that adds backends to be disabled
kratsg Sep 20, 2023
360282d
typo
kratsg Sep 20, 2023
079d130
fix up
kratsg Sep 20, 2023
67ab857
Update tests/conftest.py
kratsg Oct 5, 2023
65a2392
Merge branch 'main' into feat/disableBackendInTests
kratsg Oct 5, 2023
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48 changes: 38 additions & 10 deletions tests/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,17 @@
import pyhf


def pytest_addoption(parser):
parser.addoption(
"--disable-backend",
action="append",
type=str,
default=[],
choices=["tensorflow", "pytorch", "jax", "minuit"],
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Suggested change
choices=["tensorflow", "pytorch", "jax", "minuit"],
choices=["numpy", "tensorflow", "pytorch", "jax", "minuit"],

Is there a reason to not include numpy?

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Numpy is a core dependency, not an optional one.

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Yes, but I would think that if I have the ability to disable backends during testing that I should be able to disable any of them, not just optional ones.

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The point of the issue was to only disable optional ones.

That was the original case yes, but is there any technical reason to not want to also be able to skip numpy?

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I don't want to delay this anymore so I'll merge this in and open an Issue.

help="list of backends to disable in tests",
)


# Factory as fixture pattern
@pytest.fixture
def get_json_from_tarfile():
Expand Down Expand Up @@ -59,14 +70,14 @@ def reset_backend():
@pytest.fixture(
scope='function',
params=[
(pyhf.tensor.numpy_backend(), None),
(pyhf.tensor.pytorch_backend(), None),
(pyhf.tensor.pytorch_backend(precision='64b'), None),
(pyhf.tensor.tensorflow_backend(), None),
(pyhf.tensor.jax_backend(), None),
(("numpy_backend", dict()), ("scipy_optimizer", dict())),
(("pytorch_backend", dict()), ("scipy_optimizer", dict())),
(("pytorch_backend", dict(precision="64b")), ("scipy_optimizer", dict())),
(("tensorflow_backend", dict()), ("scipy_optimizer", dict())),
(("jax_backend", dict()), ("scipy_optimizer", dict())),
(
pyhf.tensor.numpy_backend(poisson_from_normal=True),
pyhf.optimize.minuit_optimizer(),
("numpy_backend", dict(poisson_from_normal=True)),
("minuit_optimizer", dict()),
),
],
ids=['numpy', 'pytorch', 'pytorch64', 'tensorflow', 'jax', 'numpy_minuit'],
Expand All @@ -87,13 +98,26 @@ def backend(request):
only_backends = [
pid for pid in param_ids if request.node.get_closest_marker(f'only_{pid}')
]
disable_backend = any(
backend in param_id for backend in request.config.option.disable_backend
)

if skip_backend and (param_id in only_backends):
raise ValueError(
f"Must specify skip_{param_id} or only_{param_id} but not both!"
)

if skip_backend:
if disable_backend:
pytest.skip(
f"skipping {func_name} as the backend is disabled via "
+ " ".join(
[
f"--disable-backend {choice}"
for choice in request.config.option.disable_backend
]
)
)
elif skip_backend:
pytest.skip(f"skipping {func_name} as specified")
elif only_backends and param_id not in only_backends:
pytest.skip(
Expand All @@ -109,10 +133,14 @@ def backend(request):
pytest.mark.xfail(reason=f"expect {func_name} to fail as specified")
)

tensor_config, optimizer_config = request.param

tensor = getattr(pyhf.tensor, tensor_config[0])(**tensor_config[1])
optimizer = getattr(pyhf.optimize, optimizer_config[0])(**optimizer_config[1])
# actual execution here, after all checks is done
pyhf.set_backend(*request.param)
pyhf.set_backend(tensor, optimizer)

yield request.param
yield (tensor, optimizer)


@pytest.fixture(
Expand Down