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