Sync v2.0 version of code to github repo

fastdeploy/model_executor/layers/quantization/w4a8.py

@@ -0,0 +1,42 @@
+"""
+# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+from typing import Optional
+
+from ..moe import FusedMoE
+from .quant_base import QuantConfigBase, QuantMethodBase
+
+
+class W4A8Config(QuantConfigBase):
+    """
+    quantization config for weight 4bits and activation 8bits
+    """
+
+    def __init__(self) -> None:
+        super().__init__()
+
+    def name(self) -> str:
+        return "w4a8"
+
+    @classmethod
+    def from_config(cls, config: dict) -> "W4A8Config":
+        return cls()
+
+    def get_quant_method(self, layer) -> Optional[QuantMethodBase]:
+        if isinstance(layer, FusedMoE):
+            from fastdeploy.model_executor.layers.moe.fused_moe_cutlass_backend import CutlassW4A8MoEMethod
+            return CutlassW4A8MoEMethod(self)
+        else:
+            raise ValueError(f"Unsupported layer type {type(layer)} for w4a8")