Typecheck negative cosine similarity

pyproject.toml

@@ -192,7 +192,6 @@ exclude = '''(?x)(
     lightly/cli/train_cli.py |
     lightly/cli/_cli_simclr.py |
     lightly/cli/_helpers.py |
-    lightly/loss/negative_cosine_similarity.py |
     lightly/loss/hypersphere_loss.py |
     lightly/loss/dino_loss.py |
     lightly/loss/sym_neg_cos_sim_loss.py |
@@ -244,7 +243,6 @@ exclude = '''(?x)(
     tests/UNMOCKED_end2end_tests/delete_datasets_test_unmocked_cli.py |
     tests/UNMOCKED_end2end_tests/create_custom_metadata_from_input_dir.py |
     tests/UNMOCKED_end2end_tests/scripts_for_reproducing_problems/test_api_latency.py |
-    tests/loss/test_NegativeCosineSimilarity.py |
     tests/loss/test_DINOLoss.py |
     tests/loss/test_VICRegLLoss.py |
     tests/loss/test_CO2Regularizer.py |

tests/loss/test_NegativeCosineSimilarity.py → tests/loss/test_negative_cosine_similarity.py

@@ -1,12 +1,11 @@
-import unittest
-
+import pytest
 import torch
 
 from lightly.loss import NegativeCosineSimilarity
 
 
-class TestNegativeCosineSimilarity(unittest.TestCase):
-    def test_forward_pass(self):
+class TestNegativeCosineSimilarity:
+    def test_forward_pass(self) -> None:
         loss = NegativeCosineSimilarity()
         for bsz in range(1, 20):
             x0 = torch.randn((bsz, 32))
@@ -15,10 +14,10 @@ def test_forward_pass(self):
             # symmetry
             l1 = loss(x0, x1)
             l2 = loss(x1, x0)
-            self.assertAlmostEqual((l1 - l2).pow(2).item(), 0.0)
+            assert l1 == pytest.approx(l2, abs=1e-5)
 
-    @unittest.skipUnless(torch.cuda.is_available(), "Cuda not available")
-    def test_forward_pass_cuda(self):
+    @pytest.mark.skipif(not torch.cuda.is_available(), reason="No cuda")
+    def test_forward_pass_cuda(self) -> None:
         loss = NegativeCosineSimilarity()
         for bsz in range(1, 20):
             x0 = torch.randn((bsz, 32)).cuda()
@@ -27,4 +26,4 @@ def test_forward_pass_cuda(self):
             # symmetry
             l1 = loss(x0, x1)
             l2 = loss(x1, x0)
-            self.assertAlmostEqual((l1 - l2).pow(2).item(), 0.0)
+            assert l1 == pytest.approx(l2, abs=1e-5)