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This commit is contained in:
95
utils/check_config_docstrings.py
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95
utils/check_config_docstrings.py
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# Copyright 2022 The HuggingFace Inc. team.
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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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import inspect
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import re
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from transformers.utils import direct_transformers_import
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CHECKER_CONFIG = {
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"name": "config_docstrings",
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"label": "Config docstrings",
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# Approximate: iterates CONFIG_MAPPING at runtime via inspect.getsource(), not cache globs.
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# Only configs registered in CONFIG_MAPPING are checked; deprecated models are skipped.
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"cache_globs": ["src/transformers/models/**/configuration_*.py"],
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"check_args": [],
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"fix_args": None,
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}
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# All paths are set with the intent you should run this script from the root of the repo with the command
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# python utils/check_config_docstrings.py
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PATH_TO_TRANSFORMERS = "src/transformers"
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# This is to make sure the transformers module imported is the one in the repo.
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transformers = direct_transformers_import(PATH_TO_TRANSFORMERS)
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CONFIG_MAPPING = transformers.models.auto.configuration_auto.CONFIG_MAPPING
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# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
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# For example, `[google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased)`
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_re_checkpoint = re.compile(r"""(?s)@auto_docstring\(.*?checkpoint\s*=\s*["']([^"']+)["']""")
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CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK = {
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"DecisionTransformerConfig",
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"EncoderDecoderConfig",
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"MusicgenConfig",
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"RagConfig",
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"SpeechEncoderDecoderConfig",
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"TimmBackboneConfig",
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"TimmWrapperConfig",
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"VisionEncoderDecoderConfig",
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"VisionTextDualEncoderConfig",
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"GraniteConfig",
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"GraniteMoeConfig",
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"GraniteMoeHybridConfig",
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"Qwen3MoeConfig",
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"GraniteSpeechConfig",
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}
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def get_checkpoint_from_config_class(config_class):
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# source code of `config_class`
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config_source = inspect.getsource(config_class)
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checkpoints = _re_checkpoint.findall(config_source)
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return checkpoints[0] if checkpoints else None
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def check_config_docstrings_have_checkpoints():
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configs_without_checkpoint = []
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for config_class in list(CONFIG_MAPPING.values()):
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# Skip deprecated models
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if "models.deprecated" in config_class.__module__:
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continue
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checkpoint = get_checkpoint_from_config_class(config_class)
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name = config_class.__name__
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if checkpoint is None and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
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configs_without_checkpoint.append(name)
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if len(configs_without_checkpoint) > 0:
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message = "\n".join(sorted(configs_without_checkpoint))
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raise ValueError(
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f"The following configurations don't contain any valid checkpoint:\n{message}\n\n"
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"The requirement is to include a link pointing to one of the models of this architecture in the "
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"docstring of the config classes listed above. The link should be passed to an `auto_docstring`"
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"decorator as follows `@auto_docstring(checkpoint='myorg/mymodel')."
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)
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if __name__ == "__main__":
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check_config_docstrings_have_checkpoints()
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