[Bugfix] Fix import of CutlassExpertsFp8 in compressed_tensors_moe.py (#20381)

Signed-off-by: Bill Nell <bnell@redhat.com>

Author: bnellnm

vllm/model_executor/layers/quantization/compressed_tensors/compressed_tensors_moe.py

@@ -14,9 +14,9 @@
 from vllm import _custom_ops as ops
 from vllm.logger import init_logger
 from vllm.model_executor.layers.fused_moe import (
-    CutlassExpertsFp8, FusedMoE, FusedMoEActivationFormat, FusedMoEConfig,
-    FusedMoEMethodBase, FusedMoEPermuteExpertsUnpermute,
-    FusedMoEPrepareAndFinalize, FusedMoeWeightScaleSupported, fused_experts)
+    FusedMoE, FusedMoEActivationFormat, FusedMoEConfig, FusedMoEMethodBase,
+    FusedMoEPermuteExpertsUnpermute, FusedMoEPrepareAndFinalize,
+    FusedMoeWeightScaleSupported)
 from vllm.model_executor.layers.quantization.compressed_tensors.schemes.compressed_tensors_wNa16 import (  # noqa
     WNA16_SUPPORTED_BITS, WNA16_SUPPORTED_TYPES_MAP)
 from vllm.model_executor.layers.quantization.utils import replace_parameter
@@ -570,6 +570,7 @@ def process_weights_after_loading(self, layer: torch.nn.Module) -> None:
             del layer.w2_input_scale
             self.fused_experts_func = None
         else:
+            from vllm.model_executor.layers.fused_moe import fused_experts
             self.fused_experts_func = fused_experts
 
     def apply(
@@ -826,6 +827,7 @@ def select_gemm_impl(
         prepare_finalize: FusedMoEPrepareAndFinalize,
         moe: FusedMoEConfig,
     ) -> FusedMoEPermuteExpertsUnpermute:
+        from vllm.model_executor.layers.fused_moe import CutlassExpertsFp8
 
         use_batched_format = (prepare_finalize.activation_format ==
                               FusedMoEActivationFormat.BatchedExperts)

vllm/model_executor/layers/quantization/fp8.py

@@ -14,10 +14,9 @@
 from vllm.distributed import get_tensor_model_parallel_world_size
 from vllm.logger import init_logger
 from vllm.model_executor.layers.fused_moe import (
-    BatchedTritonOrDeepGemmExperts, FusedMoE, FusedMoEActivationFormat,
-    FusedMoEConfig, FusedMoEMethodBase, FusedMoEPermuteExpertsUnpermute,
-    FusedMoEPrepareAndFinalize, FusedMoeWeightScaleSupported,
-    TritonOrDeepGemmExperts)
+    FusedMoE, FusedMoEActivationFormat, FusedMoEConfig, FusedMoEMethodBase,
+    FusedMoEPermuteExpertsUnpermute, FusedMoEPrepareAndFinalize,
+    FusedMoeWeightScaleSupported)
 from vllm.model_executor.layers.linear import (LinearBase, LinearMethodBase,
                                                UnquantizedLinearMethod)
 from vllm.model_executor.layers.quantization import QuantizationMethods
@@ -785,6 +784,9 @@ def select_gemm_impl(
         prepare_finalize: FusedMoEPrepareAndFinalize,
         moe: FusedMoEConfig,
     ) -> FusedMoEPermuteExpertsUnpermute:
+        from vllm.model_executor.layers.fused_moe import (
+            BatchedTritonOrDeepGemmExperts, TritonOrDeepGemmExperts)
+
         assert not self.use_marlin and not self.rocm_aiter_moe_enabled, (
             "Marlin and ROCm AITER are not supported with all2all yet.")