[CI Fix] Pin deepep and pplx tags in tools/ep_kernels/, gate multigpu tests (#23568)

Signed-off-by: mgoin <mgoin64@gmail.com>

tests/kernels/moe/test_deepep_deepgemm_moe.py

@@ -23,6 +23,7 @@ from vllm.utils import has_deep_ep, has_deep_gemm
 from vllm.utils.deep_gemm import (is_blackwell_deep_gemm_e8m0_used,
                                   is_deep_gemm_supported)
 
+from ...utils import multi_gpu_test
 from .parallel_utils import ProcessGroupInfo, parallel_launch
 from .utils import make_test_weights
 
@@ -370,6 +371,7 @@ NUM_EXPERTS = [32]
 @pytest.mark.parametrize("num_experts", NUM_EXPERTS)
 @pytest.mark.parametrize("topk", TOPKS)
 @pytest.mark.parametrize("world_dp_size", [(2, 1)])
+@multi_gpu_test(num_gpus=2)
 @requires_deep_ep
 @requires_deep_gemm
 @pytest.mark.skipif(is_blackwell_deep_gemm_e8m0_used(),
@@ -427,6 +429,7 @@ USE_FP8_DISPATCH = [False]
 @pytest.mark.parametrize("use_fp8_dispatch", USE_FP8_DISPATCH)
 @pytest.mark.parametrize("block_size", [[128, 128]])
 @pytest.mark.parametrize("world_dp_size", [(2, 1)])
+@multi_gpu_test(num_gpus=2)
 @requires_deep_ep
 @requires_deep_gemm
 @pytest.mark.skipif(is_blackwell_deep_gemm_e8m0_used(),

tests/kernels/moe/test_deepep_moe.py

@@ -24,6 +24,7 @@ from vllm.model_executor.layers.quantization.utils.fp8_utils import (
 from vllm.platforms import current_platform
 from vllm.utils import has_deep_ep
 
+from ...utils import multi_gpu_test
 from .parallel_utils import ProcessGroupInfo, parallel_launch
 
 if has_deep_ep():
@@ -411,6 +412,7 @@ DTYPES = [torch.bfloat16, torch.float8_e4m3fn]
 @pytest.mark.parametrize("topk", [6])
 @pytest.mark.parametrize("world_dp_size", [(2, 1)])
 @pytest.mark.parametrize("per_act_token_quant", [False, True])
+@multi_gpu_test(num_gpus=2)
 @requires_deep_ep
 def test_deep_ep_moe(
     dtype: torch.dtype,
@@ -459,6 +461,7 @@ USE_FP8_DISPATCH = [True, False]
 @pytest.mark.parametrize("topk", [6])
 @pytest.mark.parametrize("world_dp_size", [(2, 1)])
 @pytest.mark.parametrize("use_fp8_dispatch", USE_FP8_DISPATCH)
+@multi_gpu_test(num_gpus=2)
 @requires_deep_ep
 def test_low_latency_deep_ep_moe(dtype: torch.dtype, mnk: tuple[int, int, int],
                                  num_experts: int, topk: int,

tests/kernels/moe/test_modular_kernel_combinations.py

@@ -16,6 +16,7 @@ from vllm.model_executor.layers.fused_moe.config import FusedMoEQuantConfig
 from vllm.utils import has_deep_ep, has_deep_gemm, has_pplx
 from vllm.utils.flashinfer import has_flashinfer_cutlass_fused_moe
 
+from ...utils import multi_gpu_test
 from .modular_kernel_tools.common import (Config, RankTensors, WeightTensors,
                                           reference_moe_impl,
                                           run_modular_kernel)
@@ -162,6 +163,7 @@ def is_nyi_config(config: Config) -> bool:
     product(MK_MULTI_GPU_PREPARE_FINALIZE_TYPES, MK_FUSED_EXPERT_TYPES))
 @pytest.mark.parametrize("fused_moe_chunk_size", FUSED_MOE_CHUNK_SIZEs)
 @pytest.mark.parametrize("world_size", [2])
+@multi_gpu_test(num_gpus=2)
 @meets_multi_gpu_requirements
 def test_modular_kernel_combinations_multigpu(
         k: int, n: int, e: int, dtype: torch.dtype,

tests/kernels/moe/test_pplx_cutlass_moe.py

@@ -17,6 +17,7 @@ from vllm.model_executor.layers.fused_moe.modular_kernel import (
 from vllm.platforms import current_platform
 from vllm.utils import cdiv
 
+from ...utils import multi_gpu_test
 from .parallel_utils import ProcessGroupInfo, parallel_launch
 
 try:
@@ -247,6 +248,7 @@ def _pplx_moe(
 @pytest.mark.parametrize("per_out_ch", [True, False])
 @pytest.mark.parametrize("world_dp_size", [[2, 1]])  #, [4, 2]])
 @pytest.mark.parametrize("use_internode", [False])
+@multi_gpu_test(num_gpus=2)
 @pytest.mark.skipif(
     (lambda x: x is None or not ops.cutlass_group_gemm_supported(x.to_int()))(
         current_platform.get_device_capability()),

tests/kernels/moe/test_pplx_moe.py

@@ -37,6 +37,7 @@ from vllm.model_executor.layers.fused_moe.topk_weight_and_reduce import (
 from vllm.platforms import current_platform
 from vllm.utils import round_up
 
+from ...utils import multi_gpu_test
 from .parallel_utils import ProcessGroupInfo, parallel_launch
 
 requires_pplx = pytest.mark.skipif(
@@ -452,6 +453,7 @@ def _pplx_prepare_finalize(
 @pytest.mark.parametrize("use_internode", [False])
 @pytest.mark.optional
 @requires_pplx
+@multi_gpu_test(num_gpus=2)
 def test_pplx_prepare_finalize_slow(
     mnk: tuple[int, int, int],
     e: int,
@@ -740,6 +742,7 @@ def _pplx_moe(
 @pytest.mark.parametrize("use_internode", [False])
 @pytest.mark.optional
 @requires_pplx
+@multi_gpu_test(num_gpus=2)
 def test_pplx_moe_slow(
     mnk: tuple[int, int, int],
     e: int,
@@ -880,6 +883,7 @@ def _pplx_test_loop(pgi: ProcessGroupInfo, dp_size: int, use_internode: bool,
 @pytest.mark.parametrize("world_dp_size", [[2, 1]])
 @pytest.mark.parametrize("use_internode", [False])
 @requires_pplx
+@multi_gpu_test(num_gpus=2)
 def test_pplx_prepare_finalize(
     world_dp_size: tuple[int, int],
     use_internode: bool,
@@ -893,6 +897,7 @@ def test_pplx_prepare_finalize(
 @pytest.mark.parametrize("world_dp_size", [[2, 1]])
 @pytest.mark.parametrize("use_internode", [False])
 @requires_pplx
+@multi_gpu_test(num_gpus=2)
 def test_pplx_moe(
     world_dp_size: tuple[int, int],
     use_internode: bool,