Merge remote-tracking branch 'origin/main' into check_tests

Author: DaloroAT

.github/workflows/pre-commit-workflow.yaml

@@ -21,7 +21,7 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v3
       with:
-        python-version: "3.8.0"
+        python-version: "3.10.0"
     - name: Install test dependencies
       run: |
         apt-get get update && apt-get install cmake

.pre-commit-config.yaml

@@ -3,49 +3,58 @@ default_stages:
 repos:
 # general hooks to verify or beautify code
 - repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v3.3.0
+  rev: v5.0.0
   hooks:
   - id: check-added-large-files
     args: [--maxkb=5000]
+    stages: [commit]
   - id: trailing-whitespace
+    stages: [commit]
   - id: check-json
+    stages: [commit]
   - id: check-merge-conflict
+    stages: [commit]
   - id: check-xml
+    stages: [commit]
   - id: check-yaml
+    stages: [commit]
   - id: detect-private-key
+    stages: [commit]
   - id: mixed-line-ending
+    stages: [commit]
   - id: pretty-format-json
     args: [--autofix]
     exclude: \.ipynb$
+    stages: [commit]
 
 
 # autoformat code with black formatter
 - repo: https://github.com/psf/black
-  rev: 22.3.0
+  rev: 25.1.0
   hooks:
   - id: black
     args: [-l 120]
 
 
 # beautify and sort imports
 - repo: https://github.com/pycqa/isort
-  rev: 5.12.0
+  rev: 6.0.0
   hooks:
   - id: isort
     args: ["--profile", "black"]
 
 
 # check code style
 - repo: https://github.com/pycqa/flake8
-  rev: 3.8.4
+  rev: 7.1.1
   hooks:
   - id: flake8
     exclude: __init__.py
 
 
 # static type checking
 - repo: https://github.com/pre-commit/mirrors-mypy
-  rev: v0.910
+  rev: v1.14.1
   hooks:
   - id: mypy
     additional_dependencies: [types-requests==2.25.9]

ci/requirements_tests.txt

@@ -1,3 +1,3 @@
 pytest>=7.2
-pre-commit==2.15.0
+pre-commit==3.5.0
 python-dotenv>=0.17.0

oml/miners/inbatch_nhard_tri.py

@@ -123,9 +123,9 @@ def _sample_from_distmat(
         hardest_negative = ids_smallest_distance[idx_anch_neg_reduced, idx_neg_sorted_by_dist]
         idx_anch_neg = all_ids_reduced[idx_anch_neg_reduced]
 
-        ids_a = []
-        ids_p = []
-        ids_n = []
+        ids_a: List[int] = []
+        ids_p: List[int] = []
+        ids_n: List[int] = []
 
         for idx_anch in torch.arange(len(labels), device=distmat.device)[torch.logical_not(ignore_anchor_mask)]:
             positives = hardest_positive[idx_anch_pos == idx_anch][self.positive_slice]

tests/test_oml/test_ddp/test_loader_patcher.py

@@ -17,6 +17,7 @@
 from .utils import run_in_ddp
 
 
+@pytest.mark.skip(reason="Dead locks may appear when running in CI")
 @pytest.mark.long
 @pytest.mark.parametrize("n_labels_sampler", [2, 5])
 @pytest.mark.parametrize("n_instances_sampler", [2, 5])
@@ -155,6 +156,7 @@ def check_patching_balance_batch_sampler(
     assert len(set(outputs_from_epochs)) == len(outputs_from_epochs)
 
 
+@pytest.mark.skip(reason="Dead locks may appear when running in CI")
 @pytest.mark.long
 @pytest.mark.parametrize("shuffle", [True, False])
 @pytest.mark.parametrize("drop_last", [True, False])

tests/test_oml/test_miners/shared_checkers.py

@@ -19,7 +19,7 @@ def check_triplets_consistency(
 
     assert num_sampled_tri == len(ids_pos) == len(ids_neg)
 
-    for (i_a, i_p, i_n) in zip(ids_anchor, ids_pos, ids_neg):
+    for i_a, i_p, i_n in zip(ids_anchor, ids_pos, ids_neg):
         assert len({i_a, i_p, i_n}) == 3
         assert labels[i_a] == labels[i_p]
         assert labels[i_a] != labels[i_n]

tests/test_oml/test_miners/test_inbatch_all_tri.py

@@ -32,7 +32,7 @@ def test_all_triplets_miner(features_and_labels: List[Tuple[torch.Tensor, List[i
 
 @pytest.mark.long
 def test_compare_all_triplets_miner_with_naive_version(
-    features_and_labels: List[Tuple[torch.Tensor, List[int]]]
+    features_and_labels: List[Tuple[torch.Tensor, List[int]]],
 ) -> None:
     max_tri = sys.maxsize
     miner = AllTripletsMiner(max_output_triplets=max_tri)

tests/test_oml/test_models/test_visualisations.py

@@ -36,7 +36,7 @@ def get_numpy_image() -> np.ndarray:
 def test_visualisation(draw_function: Any, image: Union[np.ndarray, Image.Image]) -> None:
     image_modified = draw_function(image)
 
-    assert type(image_modified) == type(image)
+    assert isinstance(image_modified, type(image))
 
     image_modified = np.array(image_modified)
 

tests/test_runs/test_ddp_cases/test_experiments_equality.py

@@ -84,7 +84,7 @@ def test_epochs_are_equal() -> None:
 
 def is_equal_models(model1: nn.Module, model2: nn.Module) -> Tuple[bool, List[torch.Tensor]]:
     for module1, module2 in zip(model1.modules(), model2.modules()):
-        assert type(module1) == type(module2)
+        assert isinstance(module1, type(module2))
         if isinstance(module1, nn.Linear):
             if not torch.all(torch.isclose(module1.weight, module2.weight, atol=TORCH_EPS)):
                 return False, [module1.weight, module2.weight]

tests/utils.py

@@ -36,5 +36,6 @@ def forward(self, x):  # type: ignore
         x = x.float()
         return x
 
+    @property
     def feat_dim(self) -> int:
         return self.model.embedding_dim