test(codspeed): remove numerous decorators for investigation

frgfm · Aug 29, 2024 · 7dcc0d4 · 7dcc0d4
1 parent 2794c71
commit 7dcc0d4
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Showing 4 changed files with 0 additions and 10 deletions.
diff --git a/tests/test_methods_activation.py b/tests/test_methods_activation.py
@@ -45,7 +45,6 @@ def _verify_cam(activation_map, output_size):
         ("ISCAM", "features.16.conv.3", None, 4, (7, 7), 1),
     ],
 )
-@pytest.mark.benchmark
 def test_img_cams(
     cam_name,
     target_layer,
@@ -76,7 +75,6 @@ def test_img_cams(
         _verify_cam(extractor(list(range(batch_size)), scores)[0], (batch_size, *output_size))
 
 
-@pytest.mark.benchmark
 def test_cam_conv1x1(mock_fullyconv_model):
     with activation.CAM(mock_fullyconv_model, fc_layer="1") as extractor, torch.no_grad():
         scores = mock_fullyconv_model(torch.rand((1, 3, 32, 32)))
@@ -93,7 +91,6 @@ def test_cam_conv1x1(mock_fullyconv_model):
         ("ISCAM", "0.3", 4, (1, 8, 16, 16)),
     ],
 )
-@pytest.mark.benchmark
 def test_video_cams(
     cam_name,
     target_layer,

diff --git a/tests/test_methods_core.py b/tests/test_methods_core.py
@@ -64,7 +64,6 @@ def test_cam_precheck(mock_img_model, mock_img_tensor):
         ((8, 8, 8, 8), 3),
     ],
 )
-@pytest.mark.benchmark
 def test_cam_normalize(input_shape, spatial_dims):
     input_tensor = torch.rand(input_shape)
     normalized_tensor = core._CAM._normalize(input_tensor, spatial_dims)
@@ -102,7 +101,6 @@ def test_cam_repr(mock_img_model):
         assert repr(extractor) == "_CAM(target_layer=['0.3'])"
 
 
-@pytest.mark.benchmark
 def test_fuse_cams():
     with pytest.raises(TypeError):
         core._CAM.fuse_cams(torch.zeros((3, 32, 32)))

diff --git a/tests/test_methods_gradient.py b/tests/test_methods_gradient.py
@@ -25,7 +25,6 @@ def _verify_cam(activation_map, output_size):
         ("LayerCAM", "features.18.0", (7, 7), 2),
     ],
 )
-@pytest.mark.benchmark
 def test_img_cams(cam_name, target_layer, output_size, batch_size, mock_img_tensor):
     model = mobilenet_v2(weights=None).eval()
     for p in model.parameters():
@@ -73,7 +72,6 @@ def test_img_cams(cam_name, target_layer, output_size, batch_size, mock_img_tens
         ("LayerCAM", "0.3", (1, 8, 16, 16)),
     ],
 )
-@pytest.mark.benchmark
 def test_video_cams(cam_name, target_layer, output_size, mock_video_model, mock_video_tensor):
     model = mock_video_model.eval()
     # Hook the corresponding layer in the model

diff --git a/tests/test_methods_utils.py b/tests/test_methods_utils.py
@@ -1,10 +1,8 @@
-import pytest
 from torchvision.models import mobilenet_v3_large, resnet18
 
 from torchcam.methods import _utils
 
 
-@pytest.mark.benchmark
 def test_locate_candidate_layer(mock_img_model):
     # ResNet-18
     mod = resnet18().eval()
@@ -26,7 +24,6 @@ def test_locate_candidate_layer(mock_img_model):
     assert mod.training
 
 
-@pytest.mark.benchmark
 def test_locate_linear_layer(mock_img_model):
     # ResNet-18
     mod = resnet18().eval()