7330416de3
### What this PR does / why we need it? It fixes following bugs: 1. When searching a specific linear quantization implementation from a tool (such as MindIE-Turbo), the mapping of packed linear is required to identify correponding quant type. 2. The exception is narrowed down to ImportError when importing MindIETurboQuantizer to better throw other errors. 3. The api of AscendKVCacheMethod.apply is aligned with that in AscendAttentionBackendImpl. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By performing offline inference:  --------- Signed-off-by: angazenn <zengyanjia@huawei.com> Co-authored-by: angazenn <zengyanjia@huawei.com>
57 lines
1.9 KiB
Python
57 lines
1.9 KiB
Python
#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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# This file is a part of the vllm-ascend project.
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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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import importlib
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from typing import Any, Dict, List, Optional
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CUSTOMIZED_QUANTIZER_TYPE: List[str] = []
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class AscendQuantizer:
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"""An interface to different quantization implementations for ascend hardwares."""
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@classmethod
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def get_quantizer(cls,
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quant_config: Dict[str, Any],
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prefix: str,
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packed_modules_mapping: Optional[Dict[str,
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Any]] = dict()):
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# TODO: Need a param to choose quantization algorithms.
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quantization_algorithm = ''
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if quantization_algorithm in CUSTOMIZED_QUANTIZER_TYPE:
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return
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try:
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module = importlib.import_module("mindie_turbo")
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MindIETurboQuantizer = module.MindIETurboQuantizer
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except ImportError:
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raise NotImplementedError(
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"There is no available ascend quantizer.")
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return MindIETurboQuantizer.get_quantizer(quant_config, prefix,
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packed_modules_mapping)
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def build_linear_method(self):
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raise NotImplementedError
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def build_moe_method(self):
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raise NotImplementedError
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def build_attention_method(self):
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raise NotImplementedError
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