99aedaff63
### What this PR does / why we need it?
**Scope of Changes**:
| File Path |
| :--- |
|` vllm_ascend/quantization/compressed_tensors/compressed_tensors.py`|
|` vllm_ascend/quantization/quant_config.py`|
|` vllm_ascend/quantization/utils.py`|
|` vllm_ascend/quantization/w4a16.py`|
|` vllm_ascend/quantization/w4a4_flatquant_dynamic.py`|
|` vllm_ascend/quantization/w4a8_dynamic.py`|
|` vllm_ascend/quantization/w8a16.py`|
|` vllm_ascend/quantization/w8a8.py`|
|` vllm_ascend/quantization/w8a8_dynamic.py`|
|` vllm_ascend/quantization/w8a8_pdmix.py`|
|` vllm_ascend/quantization/w8a8mxfp8.py`|
|` vllm_ascend/sample/rejection_sampler.py`|
|` vllm_ascend/sample/sampler.py`|
|` vllm_ascend/worker/block_table.py`|
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
2c24bc6996
Signed-off-by: MrZ20 <2609716663@qq.com>
63 lines
2.0 KiB
Python
63 lines
2.0 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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from typing import Any
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# Registry: maps (quant_type, layer_type) -> SchemeClass
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_SCHEME_REGISTRY: dict[tuple[str, str], type[Any]] = {}
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def register_scheme(quant_type: str, layer_type: str):
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"""Decorator to register a quantization scheme.
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Args:
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quant_type: Quantization type (e.g., "W8A8", "W8A8_DYNAMIC").
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layer_type: Layer type (e.g., "linear", "moe").
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Returns:
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Decorator function that registers the class.
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Example:
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@register_scheme("W8A8_DYNAMIC", "linear")
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class W8A8DynamicLinearScheme(AscendLinearScheme):
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...
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"""
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def decorator(cls: type[Any]) -> type[Any]:
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key = (quant_type, layer_type)
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if key in _SCHEME_REGISTRY:
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raise ValueError(
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f"Scheme already registered for {quant_type}/{layer_type}: {_SCHEME_REGISTRY[key].__name__}"
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)
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_SCHEME_REGISTRY[key] = cls
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return cls
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return decorator
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def get_scheme_class(quant_type: str, layer_type: str) -> type[Any] | None:
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"""Get scheme class for given quant_type and layer_type.
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Args:
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quant_type: Quantization type (e.g., "W8A8", "W8A8_DYNAMIC").
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layer_type: Layer type (e.g., "linear", "moe").
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Returns:
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The registered scheme class, or None if not found.
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"""
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return _SCHEME_REGISTRY.get((quant_type, layer_type))
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