Files
enginex-ascend-910-vllm/vllm_ascend/quantization/methods/__init__.py
Sun Ruoxi 7f8a1b1f7a init v0.23.0
Signed-off-by: Sun Ruoxi <sunruoxi@4paradigm.com>
2026-08-27 15:11:51 +08:00

104 lines
4.0 KiB
Python

#
# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
# This file is a part of the vllm-ascend project.
#
# 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.
#
"""Ascend quantization scheme implementations.
This module provides all quantization scheme implementations for Ascend NPU.
Schemes are automatically registered via the @register_scheme decorator.
Usage:
from vllm_ascend.quantization.methods import get_scheme_class
# Get a scheme class by quant_type and layer_type
scheme_cls = get_scheme_class("W8A8_DYNAMIC", "linear")
scheme = scheme_cls()
"""
from typing import Any
# Import base classes
from .base import AscendAttentionScheme, AscendLinearScheme, AscendMoEScheme, QuantType
# Import all scheme classes for external access
from .fp8 import AscendW4A8MXFPDSDynamicFusedMoEMethod, AscendW8A8MXFP8DSDynamicLinearMethod
from .kv_c8 import AscendFAQuantAttentionMethod
# Import registry functions
from .registry import get_scheme_class, register_scheme
from .w4a4_flatquant import AscendW4A4FlatQuantDynamicLinearMethod
from .w4a4_laos_dynamic import AscendW4A4LaosDynamicLinearMethod
from .w4a4_mxfp4 import AscendW4A4MXFP4DynamicFusedMoEMethod, AscendW4A4MXFP4DynamicLinearMethod
from .w4a4_mxfp4_flatquant import AscendW4A4MXFP4FlatQuantDynamicLinearMethod
from .w4a8 import AscendW4A8DynamicFusedMoEMethod, AscendW4A8DynamicLinearMethod
from .w4a8_mxfp4 import AscendW4A8MXFPDynamicFusedMoEMethod, AscendW4A8MXFPDynamicLinearMethod
from .w4a16 import AscendW4A16FusedMoEMethod
from .w4a16_mxfp4 import AscendW4A16MXFP4FusedMoEMethod
from .w8a8_dynamic import AscendW8A8DynamicFusedMoEMethod, AscendW8A8DynamicLinearMethod
from .w8a8_mxfp8 import AscendW8A8MXFP8DynamicLinearMethod
from .w8a8_pdmix import AscendW8A8PDMixFusedMoeMethod, AscendW8A8PDMixLinearMethod
from .w8a8_static import AscendW8A8LinearMethod
from .w8a8fp8_dynamic import AscendW8A8FP8DynamicFusedMoEMethod, AscendW8A8FP8DynamicLinearMethod
from .w8a16 import AscendW8A16LinearMethod
def is_mx_quant_type(instance: Any) -> bool:
"""Checks if the quantization method is a microscaling (MX) type."""
MX_QUANT_TYPES = (
AscendW8A8MXFP8DynamicLinearMethod,
AscendW4A4MXFP4DynamicLinearMethod,
AscendW4A4MXFP4DynamicFusedMoEMethod,
AscendW4A4MXFP4FlatQuantDynamicLinearMethod,
AscendW4A8MXFPDynamicLinearMethod,
AscendW4A8MXFPDynamicFusedMoEMethod,
AscendW4A16MXFP4FusedMoEMethod,
)
return isinstance(instance, MX_QUANT_TYPES)
__all__ = [
# Base classes
"AscendAttentionScheme",
"AscendLinearScheme",
"AscendMoEScheme",
"QuantType",
# Registry functions
"register_scheme",
"get_scheme_class",
# Utility functions
"is_mx_quant_type",
# Scheme classes
"AscendW8A8LinearMethod",
"AscendW8A8DynamicLinearMethod",
"AscendW8A8DynamicFusedMoEMethod",
"AscendW8A8FP8DynamicLinearMethod",
"AscendW8A8FP8DynamicFusedMoEMethod",
"AscendW8A8MXFP8DynamicLinearMethod",
"AscendW8A8PDMixLinearMethod",
"AscendW8A8PDMixFusedMoeMethod",
"AscendW8A16LinearMethod",
"AscendW4A8DynamicLinearMethod",
"AscendW4A8DynamicFusedMoEMethod",
"AscendW4A16FusedMoEMethod",
"AscendW4A4FlatQuantDynamicLinearMethod",
"AscendW4A4LaosDynamicLinearMethod",
"AscendFAQuantAttentionMethod",
"AscendW4A4MXFP4DynamicLinearMethod",
"AscendW4A4MXFP4DynamicFusedMoEMethod",
"AscendW4A4MXFP4FlatQuantDynamicLinearMethod",
"AscendW8A8MXFP8DSDynamicLinearMethod",
"AscendW4A8MXFPDSDynamicFusedMoEMethod",
]