7d99c2c4fd
Signed-off-by: jinzhen.ljz <jinzhen.ljz@antgroup.com> Signed-off-by: mgoin <mgoin64@gmail.com> Co-authored-by: Codex <noreply@openai.com> Co-authored-by: mgoin <mgoin64@gmail.com>
109 lines
5.3 KiB
Python
109 lines
5.3 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Lazy facade for the optional ``humming`` package.
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vLLM code should import humming symbols from here so that ``import humming``
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(which has import-time side effects) is deferred until first use. Add new
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symbols to both the ``TYPE_CHECKING`` imports and ``_EXPORTS``, using
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``"module.path:attr"`` or ``"module.path"`` for a whole-module re-export.
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"""
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import importlib
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from typing import TYPE_CHECKING, Any
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if TYPE_CHECKING:
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from humming import dtypes as dtypes
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from humming.config import GemmType as GemmType
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from humming.config import InputQuantizationMode as InputQuantizationMode
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from humming.config import LayerConfig as LayerConfig
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from humming.config import MmaType as MmaType
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from humming.config import WeightScale2Type as WeightScale2Type
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from humming.config import WeightScaleType as WeightScaleType
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from humming.dtypes import DataType as DataType
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from humming.forward import humming_forward as humming_forward
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from humming.forward import may_process_input as may_process_input
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from humming.forward import may_quant_input as may_quant_input
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from humming.ops import process_input as process_input
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from humming.schema import AWQWeightSchema as AWQWeightSchema
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from humming.schema import BaseInputSchema as BaseInputSchema
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from humming.schema import BaseWeightSchema as BaseWeightSchema
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from humming.schema import BitnetWeightSchema as BitnetWeightSchema
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from humming.schema import (
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CompressedTensorsInputSchema as CompressedTensorsInputSchema,
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)
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from humming.schema import (
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CompressedTensorsWeightSchema as CompressedTensorsWeightSchema,
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)
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from humming.schema import Fp8InputSchema as Fp8InputSchema
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from humming.schema import GptOssMxfp4WeightSchema as GptOssMxfp4WeightSchema
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from humming.schema import GPTQWeightSchema as GPTQWeightSchema
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from humming.schema import HummingInputSchema as HummingInputSchema
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from humming.schema import HummingWeightSchema as HummingWeightSchema
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from humming.schema import Mxfp4WeightSchema as Mxfp4WeightSchema
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from humming.schema.fp8 import Fp8WeightSchema as Fp8WeightSchema
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from humming.schema.modelopt import (
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ModeloptMxfp8WeightSchema as ModeloptMxfp8WeightSchema,
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)
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from humming.schema.modelopt import (
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ModeloptNvfp4InputSchema as ModeloptNvfp4InputSchema,
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)
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from humming.schema.modelopt import (
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ModeloptNvfp4WeightSchema as ModeloptNvfp4WeightSchema,
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)
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from humming.transform import prepare_layer_config as prepare_layer_config
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from humming.transform import transform_humming_tensors as transform_humming_tensors
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from humming.tune import get_heuristics_config as get_heuristics_config
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from humming.utils.weight import quantize_weight as quantize_weight
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_EXPORTS: dict[str, str] = {
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"dtypes": "humming.dtypes",
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"DataType": "humming.dtypes:DataType",
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"GemmType": "humming.config:GemmType",
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"LayerConfig": "humming.config:LayerConfig",
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"WeightScaleType": "humming.config:WeightScaleType",
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"WeightScale2Type": "humming.config:WeightScale2Type",
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"InputQuantizationMode": "humming.config:InputQuantizationMode",
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"MmaType": "humming.config:MmaType",
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"humming_forward": "humming.forward:humming_forward",
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"may_process_input": "humming.forward:may_process_input",
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"process_input": "humming.ops:process_input",
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"may_quant_input": "humming.forward:may_quant_input",
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"prepare_layer_config": "humming.transform:prepare_layer_config",
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"transform_humming_tensors": "humming.transform:transform_humming_tensors",
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"get_heuristics_config": "humming.tune:get_heuristics_config",
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"BaseInputSchema": "humming.schema:BaseInputSchema",
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"BaseWeightSchema": "humming.schema:BaseWeightSchema",
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"HummingInputSchema": "humming.schema:HummingInputSchema",
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"HummingWeightSchema": "humming.schema:HummingWeightSchema",
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"quantize_weight": "humming.utils.weight:quantize_weight",
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"AWQWeightSchema": "humming.schema:AWQWeightSchema",
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"BitnetWeightSchema": "humming.schema:BitnetWeightSchema",
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"ModeloptMxfp8WeightSchema": "humming.schema.modelopt:ModeloptMxfp8WeightSchema",
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"ModeloptNvfp4InputSchema": "humming.schema.modelopt:ModeloptNvfp4InputSchema",
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"ModeloptNvfp4WeightSchema": "humming.schema.modelopt:ModeloptNvfp4WeightSchema",
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"CompressedTensorsInputSchema": "humming.schema:CompressedTensorsInputSchema",
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"CompressedTensorsWeightSchema": "humming.schema:CompressedTensorsWeightSchema",
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"Fp8InputSchema": "humming.schema:Fp8InputSchema",
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"Fp8WeightSchema": "humming.schema.fp8:Fp8WeightSchema",
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"Mxfp4WeightSchema": "humming.schema:Mxfp4WeightSchema",
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"GptOssMxfp4WeightSchema": "humming.schema:GptOssMxfp4WeightSchema",
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"GPTQWeightSchema": "humming.schema:GPTQWeightSchema",
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}
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def __getattr__(name: str) -> Any:
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spec = _EXPORTS.get(name)
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if spec is None:
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raise AttributeError(f"module 'vllm.utils.humming' has no attribute {name!r}")
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if ":" in spec:
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mod_path, attr = spec.split(":", 1)
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obj = getattr(importlib.import_module(mod_path), attr)
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else:
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obj = importlib.import_module(spec)
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globals()[name] = obj
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return obj
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def __dir__() -> list[str]:
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return sorted({*globals(), *_EXPORTS})
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