[Perf][fp8] Use CustomOp abstraction for fp8 quant for better perf (#19830)

Signed-off-by: Luka Govedic <lgovedic@redhat.com>
Co-authored-by: mgoin <mgoin64@gmail.com>

vllm/compilation/fusion.py

@@ -1,6 +1,6 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-from typing import Callable, ClassVar, NamedTuple, Optional
+from typing import Callable, NamedTuple, Optional
 
 import torch
 import torch._inductor.pattern_matcher as pm
@@ -11,6 +11,8 @@ from torch._ops import OpOverload
 
 from vllm.config import VllmConfig
 from vllm.logger import init_logger
+from vllm.model_executor.layers.quantization.utils.quant_utils import (
+    GroupShape)
 from vllm.platforms import current_platform
 
 from .fx_utils import find_getitem_maybe
@@ -33,27 +35,6 @@ RMS_OP = torch.ops._C.rms_norm.default
 RMS_ADD_OP = torch.ops._C.fused_add_rms_norm.default
 
 
-# Use proxy as NamedTuple direct subclasses cannot have static members
-class _GroupShape(NamedTuple):
-    row: int
-    col: int
-
-
-class GroupShape(_GroupShape):
-    """
-    This class describes the quantization group shape.
-    It includes static members for common shapes (per-tensor, per-token).
-    """
-
-    # Aliases for common quantization group shapes
-    PER_TENSOR: ClassVar['GroupShape']
-    PER_TOKEN: ClassVar['GroupShape']
-
-
-GroupShape.PER_TENSOR = GroupShape(-1, -1)
-GroupShape.PER_TOKEN = GroupShape(1, -1)
-
-
 class QuantKey(NamedTuple):
     """
     Named tuple for identifying the type of quantization.