| # Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved. | |
| # | |
| # 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. | |
| from typing import Dict | |
| from compressed_tensors.transform import TransformScheme | |
| from pydantic import BaseModel, ConfigDict | |
| __all__ = ["TransformConfig"] | |
| class TransformConfig(BaseModel): | |
| """ | |
| Configuration of transforms to be applied to a model. This config is to be | |
| serialized within a model's `config.json` file | |
| :param config_groups: A dictionary of `TransformSchemes` that should be applied | |
| to a particular model. The keys can be any arbitrary string | |
| """ | |
| config_groups: Dict[str, TransformScheme] | |
| model_config = ConfigDict(extra="forbid") | |