[EZ] remove extraneous @pytest.mark.asyncio

tests/unit_tests/losses/test_grpo_loss.py

@@ -35,7 +35,6 @@ def sample_data(self):
         return logprobs, ref_logprobs, advantages, padding_mask
 
     @pytest.mark.timeout(10)
-    @pytest.mark.asyncio
     def test_forward_basic(self, loss_fn, sample_data):
         """Test basic forward pass."""
         logprobs, ref_logprobs, advantages, padding_mask = sample_data
@@ -48,7 +47,6 @@ def test_forward_basic(self, loss_fn, sample_data):
         assert not torch.isnan(loss)
 
     @pytest.mark.timeout(10)
-    @pytest.mark.asyncio
     def test_output_shape(self, loss_fn):
         """Test output shape for different input sizes."""
         for batch_size in [1, 3, 8]:
@@ -62,7 +60,6 @@ def test_output_shape(self, loss_fn):
                 assert loss.shape == torch.Size([])
 
     @pytest.mark.timeout(10)
-    @pytest.mark.asyncio
     def test_gradient_flow(self, loss_fn, sample_data):
         """Test that gradients flow through logprobs."""
         logprobs, ref_logprobs, advantages, padding_mask = sample_data
@@ -76,7 +73,6 @@ def test_gradient_flow(self, loss_fn, sample_data):
         assert torch.isfinite(logprobs.grad).all()
 
     @pytest.mark.timeout(10)
-    @pytest.mark.asyncio
     def test_no_gradient_to_ref_logprobs(self, loss_fn, sample_data):
         """Test that gradients don't flow to reference logprobs."""
         logprobs, ref_logprobs, advantages, padding_mask = sample_data
@@ -89,7 +85,6 @@ def test_no_gradient_to_ref_logprobs(self, loss_fn, sample_data):
         assert ref_logprobs.grad is not None
 
     @pytest.mark.timeout(10)
-    @pytest.mark.asyncio
     def test_padding_mask_effect(self, loss_fn):
         """Test that padding mask correctly ignores padded tokens."""
         batch_size, seq_len = 2, 4
@@ -111,7 +106,6 @@ def test_padding_mask_effect(self, loss_fn):
         assert not torch.allclose(loss_full, loss_partial)
 
     @pytest.mark.timeout(10)
-    @pytest.mark.asyncio
     def test_beta_parameter_effect(self, sample_data):
         """Test that different beta values produce different losses."""
         logprobs, ref_logprobs, advantages, padding_mask = sample_data
@@ -128,7 +122,6 @@ def test_beta_parameter_effect(self, sample_data):
             assert not torch.allclose(loss_1, loss_2, atol=1e-6)
 
     @pytest.mark.timeout(10)
-    @pytest.mark.asyncio
     def test_zero_advantages(self, loss_fn):
         """Test behavior with zero advantages."""
         batch_size, seq_len = 2, 4
@@ -144,7 +137,6 @@ def test_zero_advantages(self, loss_fn):
         assert torch.isfinite(loss)
 
     @pytest.mark.timeout(10)
-    @pytest.mark.asyncio
     def test_identical_policies(self, loss_fn):
         """Test behavior when current and reference policies are identical."""
         batch_size, seq_len = 2, 4
@@ -160,7 +152,6 @@ def test_identical_policies(self, loss_fn):
         assert torch.isfinite(loss)
 
     @pytest.mark.timeout(10)
-    @pytest.mark.asyncio
     def test_extreme_values(self, loss_fn):
         """Test with extreme but valid values."""
         batch_size, seq_len = 2, 3
@@ -179,7 +170,6 @@ def test_extreme_values(self, loss_fn):
         assert not torch.isnan(loss)
 
     @pytest.mark.timeout(10)
-    @pytest.mark.asyncio
     def test_numerical_stability(self, loss_fn):
         """Test numerical stability with edge cases."""
         batch_size, seq_len = 1, 2
@@ -195,7 +185,6 @@ def test_numerical_stability(self, loss_fn):
         assert torch.isfinite(loss)
 
     @pytest.mark.timeout(10)
-    @pytest.mark.asyncio
     def test_all_masked_sequence(self, loss_fn):
         """Test behavior when entire sequence is masked."""
         batch_size, seq_len = 1, 3
@@ -211,7 +200,6 @@ def test_all_masked_sequence(self, loss_fn):
         assert torch.isfinite(loss)
 
     @pytest.mark.timeout(10)
-    @pytest.mark.asyncio
     def test_mathematical_correctness(self, loss_fn):
         """Test mathematical correctness with simpler verification."""
         # Test with known simple case

tests/unit_tests/test_service.py

@@ -759,8 +759,7 @@ async def test_broadcast_fanout_vs_route():
 # Router Tests
 
 
-@pytest.mark.asyncio
-async def test_session_router_with_round_robin_fallback():
+def test_session_router_with_round_robin_fallback():
     """Switch fallback router to round-robin and verify assignment order."""
     # Choose RoundRobinRouter as fallback, r1 and r2 should be assigned to different replicas
     replicas = [make_replica(0, load=0), make_replica(1, load=5)]