[RFC][ROCm][AITER] Keep all AITER kernels in _aiter_ops class like _custom_ops and _ipex_ops

docs/design/moe_kernel_features.md

@@ -97,7 +97,7 @@ To be used with a particular `FusedMoEPrepareAndFinalize` sub-class, MoE kernels
 | trtllm                       | standard              | mxfp4,</br>nvfp4 | G(16),G(32)   | <sup>5</sup>                                                | N                     | Y       | [`TrtLlmGenExperts`][vllm.model_executor.layers.fused_moe.trtllm_moe.TrtLlmGenExperts]                                                                                                                                                                                                                      |
 | pallas                       | standard              | N/A              | N/A           | silu                                                        | N                     | N       | [`fused_moe`][vllm.model_executor.layers.fused_moe.moe_pallas.fused_moe]                                                                                                                                                                                                                                    |
 | iterative                    | standard              | N/A              | N/A           | silu                                                        | N                     | N       | [`fused_moe`][vllm.model_executor.layers.fused_moe.moe_torch_iterative.fused_moe]                                                                                                                                                                                                                           |
-| rocm aiter moe               | standard              | fp8              | G(128),A,T    | silu, gelu                                                  | Y                     | N       | [`rocm_aiter_fused_experts`][vllm.model_executor.layers.fused_moe.rocm_aiter_fused_moe.rocm_aiter_fused_moe_impl]                                                                                                                                                                                           |
+| rocm aiter moe               | standard              | fp8              | G(128),A,T    | silu, gelu                                                  | Y                     | N       | [`rocm_aiter_fused_experts`][vllm.model_executor.layers.fused_moe.rocm_aiter_fused_moe.rocm_aiter_fused_experts]                                                                                                                                                                                           |
 | cpu_fused_moe                | standard              | N/A              | N/A           | silu                                                        | N                     | N       | [`CPUFusedMOE`][vllm.model_executor.layers.fused_moe.cpu_fused_moe.CPUFusedMOE]                                                                                                                                                                                                                             |
 | naive batched<sup>4</sup>    | batched               | int8,</br>fp8    | G,A,T         | silu, gelu                                                  | <sup>6</sup>          | Y       | [`NaiveBatchedExperts`][vllm.model_executor.layers.fused_moe.fused_batched_moe.NaiveBatchedExperts]                                                                                                                                                                                                         |
 

tests/kernels/moe/test_moe.py

@@ -6,6 +6,8 @@
 """
 
 import functools
+import importlib
+import sys
 from collections.abc import Callable
 from dataclasses import dataclass
 from typing import Any
@@ -20,6 +22,7 @@
 import vllm.model_executor.layers.fused_moe  # noqa
 from tests.kernels.moe.utils import fused_moe
 from tests.kernels.utils import opcheck, stack_and_dev, torch_moe
+from vllm._aiter_ops import rocm_aiter_ops
 from vllm.config import VllmConfig, set_current_vllm_config
 from vllm.distributed.parallel_state import init_distributed_environment
 from vllm.forward_context import set_forward_context
@@ -412,14 +415,12 @@ def test_mixtral_moe(
     huggingface."""
 
     # clear the cache before every test
-    from vllm.model_executor.layers.fused_moe.rocm_aiter_fused_moe import (
-        is_rocm_aiter_moe_enabled,
-    )
+    # Force reload aiter_ops to pick up the new environment variables.
+    if "rocm_aiter_ops" in sys.modules:
+        importlib.reload(rocm_aiter_ops)
 
-    is_rocm_aiter_moe_enabled.cache_clear()
     if use_rocm_aiter:
         monkeypatch.setenv("VLLM_ROCM_USE_AITER", "1")
-
         if dtype == torch.float32:
             pytest.skip("AITER ROCm test skip for float32")
 

tests/model_executor/test_enabled_custom_ops.py

@@ -4,6 +4,7 @@
 import pytest
 import torch
 
+from vllm._aiter_ops import rocm_aiter_ops
 from vllm.config import CompilationConfig, VllmConfig, set_current_vllm_config
 from vllm.model_executor.custom_op import CustomOp
 from vllm.model_executor.layers.activation import (
@@ -15,9 +16,6 @@
     dispatch_topk_func,
     vllm_topk_softmax,
 )
-from vllm.model_executor.layers.fused_moe.rocm_aiter_fused_moe import (
-    is_rocm_aiter_moe_enabled,
-)
 from vllm.model_executor.layers.layernorm import (
     RMSNorm,
     dispatch_rocm_rmsnorm_func,
@@ -126,50 +124,39 @@ def test_enabled_ops_invalid(env: str):
             RMSNorm(1024).enabled()
 
 
-@pytest.mark.parametrize("use_rocm_aiter", ["0", "1"])
-def test_topk_dispatch(use_rocm_aiter: str, monkeypatch):
-    monkeypatch.setenv("VLLM_ROCM_USE_AITER", use_rocm_aiter)
-    topk_func = dispatch_topk_func()
-    is_rocm_aiter_moe_enabled.cache_clear()
-    if current_platform.is_rocm() and int(use_rocm_aiter):
-        from vllm.model_executor.layers.fused_moe.rocm_aiter_fused_moe import (
-            rocm_aiter_topk_softmax,
-        )
+@pytest.mark.parametrize(
+    "use_rocm_aiter", [True, False] if current_platform.is_rocm() else [False]
+)
+def test_topk_dispatch(use_rocm_aiter: bool):
+    topk_func = dispatch_topk_func(use_rocm_aiter)
 
-        assert topk_func == rocm_aiter_topk_softmax
+    if current_platform.is_rocm() and use_rocm_aiter:
+        assert topk_func == rocm_aiter_ops.topk_softmax
     else:
         assert topk_func == vllm_topk_softmax
 
 
 @pytest.mark.parametrize("add_residual", [True, False])
 @pytest.mark.parametrize("dtype", [torch.float32, torch.float16, torch.bfloat16])
-@pytest.mark.parametrize("use_rocm_aiter", ["0", "1"])
-@pytest.mark.parametrize("use_rocm_aiter_norm", ["0", "1"])
+@pytest.mark.parametrize("use_rocm_aiter", [True, False])
 @pytest.mark.skipif(
     not current_platform.is_rocm(), reason="AITER is a feature exclusive for ROCm"
 )
 def test_rms_norm_dispatch(
-    add_residual: bool,
-    dtype: torch.dtype,
-    use_rocm_aiter: str,
-    use_rocm_aiter_norm: str,
-    monkeypatch,
+    add_residual: bool, dtype: torch.dtype, use_rocm_aiter: bool
 ):
-    monkeypatch.setenv("VLLM_ROCM_USE_AITER", use_rocm_aiter)
-    monkeypatch.setenv("VLLM_ROCM_USE_AITER_RMSNORM", use_rocm_aiter_norm)
-    rms_norm_func = dispatch_rocm_rmsnorm_func(add_residual, dtype)
+    rms_norm_func = dispatch_rocm_rmsnorm_func(add_residual, dtype, use_rocm_aiter)
 
     should_use_rocm_aiter = (
         current_platform.is_rocm()
-        and int(use_rocm_aiter)
-        and int(use_rocm_aiter_norm)
+        and use_rocm_aiter
         and dtype in RMS_NORM_SUPPORTED_DTYPES
     )
 
     if add_residual and should_use_rocm_aiter:
-        assert rms_norm_func == torch.ops.vllm.rocm_aiter_rmsnorm2d_fwd_with_add
+        assert rms_norm_func == rocm_aiter_ops.rms_norm2d_with_add
     elif should_use_rocm_aiter:
-        assert rms_norm_func == torch.ops.vllm.rocm_aiter_rms_norm
+        assert rms_norm_func == rocm_aiter_ops.rms_norm
     elif add_residual:
         assert rms_norm_func == fused_add_rms_norm
     else: