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일반 유틸리티 (General Utilities)

이 페이지는 `utils.py` 파일에 있는 Transformers의 일반 유틸리티 함수들을 나열합니다.

이 함수들 대부분은 라이브러리의 일반적인 코드를 연구할 때만 유용합니다.

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Enums 및 namedtuples

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class transformers.utils.ExplicitEnum

< source >

( value names = None module = None qualname = None type = None start = 1 )

Enum with more explicit error message for missing values.

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class transformers.utils.PaddingStrategy

< source >

( value names = None module = None qualname = None type = None start = 1 )

Possible values for the `padding` argument in PreTrainedTokenizerBase.call(). Useful for tab-completion in an IDE.

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class transformers.TensorType

< source >

( value names = None module = None qualname = None type = None start = 1 )

Possible values for the `return_tensors` argument in PreTrainedTokenizerBase.call(). Useful for tab-completion in an IDE.

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특수 데코레이터 (Special Decorators)

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transformers.add_start_docstrings

< source >

( *docstr )

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transformers.utils.add_start_docstrings_to_model_forward

< source >

( *docstr )

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transformers.add_end_docstrings

< source >

( *docstr )

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transformers.utils.add_code_sample_docstrings

< source >

( *docstr processor_class = None checkpoint = None output_type = None config_class = None mask = '[MASK]' qa_target_start_index = 14 qa_target_end_index = 15 model_cls = None modality = None expected_output = None expected_loss = None real_checkpoint = None revision = None )

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transformers.utils.replace_return_docstrings

< source >

( output_type = None config_class = None )

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특수 속성 (Special Properties)

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class transformers.utils.cached_property

< source >

( fget = None fset = None fdel = None doc = None )

Descriptor that mimics @property but caches output in member variable.

From tensorflow_datasets

Built-in in functools from Python 3.8.

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기타 유틸리티

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class transformers.utils._LazyModule

< source >

( name: str module_file: str import_structure: Dict module_spec: ModuleSpec = None extra_objects: Dict = None )

Module class that surfaces all objects but only performs associated imports when the objects are requested.

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