diff --git a/tests/v1/generation/test_batch_invariance.py b/tests/v1/generation/test_batch_invariance.py index 6fe7c42df2830..da44f259e0e8e 100644 --- a/tests/v1/generation/test_batch_invariance.py +++ b/tests/v1/generation/test_batch_invariance.py @@ -10,6 +10,11 @@ import torch from vllm import LLM, SamplingParams from vllm.platforms import current_platform +hopper_only = pytest.mark.skipif( + not (current_platform.is_cuda() and current_platform.is_device_capability(90)), + reason="Requires CUDA and Hopper (SM90)", +) + @pytest.fixture(autouse=True) def enable_batch_invariant_mode(): @@ -66,10 +71,7 @@ def _random_prompt(min_words: int = 1024, max_words: int = 1024 * 2) -> str: return base_prompt -@pytest.mark.skipif( - not current_platform.has_device_capability(90), - reason="Batch invariance tests only supported on Hopper (SM90)", -) +@hopper_only @pytest.mark.timeout(1000) def test_v1_generation_is_deterministic_across_batch_sizes_with_needle(): """ @@ -214,14 +216,7 @@ def _extract_step_logprobs(request_output): return None, None -@pytest.mark.skipif( - not current_platform.has_device_capability(90), - reason="Batch invariance tests only supported on Hopper (SM90)", -) -@pytest.mark.skipif( - not torch.cuda.is_available(), - reason="Requires CUDA to match production inference path.", -) +@hopper_only @pytest.mark.parametrize("backend", ["FLASH_ATTN", "FLASHINFER"]) @pytest.mark.forked def test_logprobs_bitwise_batch_invariance_bs1_vs_bsN(backend): @@ -436,10 +431,7 @@ def test_logprobs_bitwise_batch_invariance_bs1_vs_bsN(backend): pytest.fail(msg) -@pytest.mark.skipif( - not current_platform.has_device_capability(90), - reason="Batch invariance tests only supported on Hopper (SM90)", -) +@hopper_only def test_simple_generation(): """ Simple test that runs the model with a basic prompt and prints the output. @@ -485,14 +477,7 @@ def test_simple_generation(): llm.shutdown() -@pytest.mark.skipif( - not current_platform.has_device_capability(90), - reason="Batch invariance tests only supported on Hopper (SM90)", -) -@pytest.mark.skipif( - not torch.cuda.is_available(), - reason="Requires CUDA to match production inference path.", -) +@hopper_only @pytest.mark.parametrize("backend", ["FLASH_ATTN", "FLASHINFER"]) @pytest.mark.forked def test_logprobs_WITHOUT_batch_invariance_should_FAIL(backend): @@ -707,14 +692,7 @@ def test_logprobs_WITHOUT_batch_invariance_should_FAIL(backend): os.environ["VLLM_KERNEL_OVERRIDE_BATCH_INVARIANT"] = old_value -@pytest.mark.skipif( - not current_platform.has_device_capability(90), - reason="Batch invariance tests only supported on Hopper (SM90)", -) -@pytest.mark.skipif( - not torch.cuda.is_available(), - reason="Requires CUDA to match production inference path.", -) +@hopper_only @pytest.mark.parametrize("backend", ["FLASH_ATTN"]) @pytest.mark.forked def test_decode_logprobs_match_prefill_logprobs(backend): diff --git a/tests/v1/generation/test_rms_norm_batch_invariant.py b/tests/v1/generation/test_rms_norm_batch_invariant.py index 12d960362430b..399965bbd734c 100644 --- a/tests/v1/generation/test_rms_norm_batch_invariant.py +++ b/tests/v1/generation/test_rms_norm_batch_invariant.py @@ -14,14 +14,13 @@ from vllm.model_executor.layers.batch_invariant import rms_norm as triton_rms_no from vllm.model_executor.layers.layernorm import RMSNorm from vllm.platforms import current_platform +hopper_only = pytest.mark.skipif( + not (current_platform.is_cuda() and current_platform.is_device_capability(90)), + reason="Requires CUDA and Hopper (SM90)", +) -@pytest.mark.skipif( - not current_platform.has_device_capability(90), - reason="Batch invariance tests only supported on Hopper (SM90)", -) -@pytest.mark.skipif( - not torch.cuda.is_available(), reason="Requires CUDA for RMS norm kernels" -) + +@hopper_only @pytest.mark.parametrize("batch_size", [1, 4, 16, 64]) @pytest.mark.parametrize("hidden_size", [512, 2048, 4096, 8192]) @pytest.mark.parametrize("dtype", [torch.float16, torch.bfloat16]) @@ -70,13 +69,7 @@ def test_rms_norm_batch_invariant_vs_standard( ) -@pytest.mark.skipif( - not current_platform.has_device_capability(90), - reason="Batch invariance tests only supported on Hopper (SM90)", -) -@pytest.mark.skipif( - not torch.cuda.is_available(), reason="Requires CUDA for RMS norm kernels" -) +@hopper_only @pytest.mark.parametrize("batch_size", [1, 16, 128]) @pytest.mark.parametrize("seq_len", [1, 32, 512]) @pytest.mark.parametrize("hidden_size", [2048, 4096]) @@ -118,13 +111,7 @@ def test_rms_norm_3d_input(batch_size: int, seq_len: int, hidden_size: int): ) -@pytest.mark.skipif( - not current_platform.has_device_capability(90), - reason="Batch invariance tests only supported on Hopper (SM90)", -) -@pytest.mark.skipif( - not torch.cuda.is_available(), reason="Requires CUDA for RMS norm kernels" -) +@hopper_only def test_rms_norm_numerical_stability(): """ Test RMS norm numerical stability with extreme values. @@ -184,13 +171,7 @@ def test_rms_norm_numerical_stability(): ) -@pytest.mark.skipif( - not current_platform.has_device_capability(90), - reason="Batch invariance tests only supported on Hopper (SM90)", -) -@pytest.mark.skipif( - not torch.cuda.is_available(), reason="Requires CUDA for RMS norm kernels" -) +@hopper_only def test_rms_norm_formula(): """ Test that RMS norm follows the correct mathematical formula. @@ -223,13 +204,7 @@ def test_rms_norm_formula(): ) -@pytest.mark.skipif( - not current_platform.has_device_capability(90), - reason="Batch invariance tests only supported on Hopper (SM90)", -) -@pytest.mark.skipif( - not torch.cuda.is_available(), reason="Requires CUDA for RMS norm kernels" -) +@hopper_only @pytest.mark.parametrize("hidden_size", [128, 1024, 4096, 16384]) def test_rms_norm_different_hidden_sizes(hidden_size: int): """ @@ -267,13 +242,7 @@ def test_rms_norm_different_hidden_sizes(hidden_size: int): ) -@pytest.mark.skipif( - not current_platform.has_device_capability(90), - reason="Batch invariance tests only supported on Hopper (SM90)", -) -@pytest.mark.skipif( - not torch.cuda.is_available(), reason="Requires CUDA for RMS norm kernels" -) +@hopper_only def test_rms_norm_determinism(): """ Test that batch-invariant RMS norm produces deterministic results.