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Remove @slow decorator in favor of @pytest.mark.slow.

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This commit is contained in:
Ryan Dick 2023-10-06 18:26:06 -04:00
parent 7870b90717
commit e0e001758a
3 changed files with 6 additions and 15 deletions
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7
docs/contributing/TESTS.md
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@ -3,7 +3,7 @@
We use `pytest` to run the backend python tests. (See [pyproject.toml](/pyproject.toml) for the default `pytest` options.)
## Fast vs. Slow
All tests are categorized as either 'fast' (no test annotation) or 'slow' (annotated with the `@slow` decorator).
All tests are categorized as either 'fast' (no test annotation) or 'slow' (annotated with the `@pytest.mark.slow` decorator).
'Fast' tests are run to validate every PR, and are fast enough that they can be run routinely during development.
@ -47,12 +47,13 @@ There are a few things to keep in mind when adding tests that depend on models.
There are several utilities to help with model setup for tests. Here is a sample test that depends on a model:
```python
import pytest
import torch
from invokeai.backend.model_management.models.base import BaseModelType, ModelType
from invokeai.backend.util.test_utils import install_and_load_model, slow
from invokeai.backend.util.test_utils import install_and_load_model
@slow
@pytest.mark.slow
def test_model(model_installer, torch_device):
model_info = install_and_load_model(
model_installer=model_installer,

10
invokeai/backend/util/test_utils.py
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@ -11,16 +11,6 @@ from invokeai.backend.model_management.model_manager import ModelInfo
from invokeai.backend.model_management.models.base import BaseModelType, ModelNotFoundException, ModelType, SubModelType
def slow(test_case):
"""Decorator for slow tests.
Tests should be marked as slow if they download a model, run model inference, or do anything else slow. To judge
whether a test is 'slow', consider how it would perform in a CPU-only environment with a low-bandwidth internet
connection.
"""
return pytest.mark.slow(test_case)
@pytest.fixture(scope="session")
def torch_device():
return "cuda" if torch.cuda.is_available() else "cpu"

4
tests/backend/ip_adapter/test_ip_adapter.py
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@ -2,7 +2,7 @@ import pytest
import torch
from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
from invokeai.backend.util.test_utils import install_and_load_model, slow
from invokeai.backend.util.test_utils import install_and_load_model
def build_dummy_sd15_unet_input(torch_device):
@ -38,7 +38,7 @@ def build_dummy_sd15_unet_input(torch_device):
},
],
)
@slow
@pytest.mark.slow
def test_ip_adapter_unet_patch(model_params, model_installer, torch_device):
"""Smoke test that IP-Adapter weights can be loaded and used to patch a UNet."""
ip_adapter_info = install_and_load_model(