General Utilities
This page lists all of Transformers general utility functions that are found in the file file_utils.py.
Most of those are only useful if you are studying the general code in the library.
Enums and namedtuples
class transformers.file_utils.ExplicitEnum
< source >( value names = None module = None qualname = None type = None start = 1 )
Enum with more explicit error message for missing values.
class transformers.file_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.
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.
Special Decorators
transformers.file_utils.add_code_sample_docstrings
< source >( *docstr processor_class = None checkpoint = None output_type = None config_class = None mask = '[MASK]' model_cls = None modality = None expected_output = '' expected_loss = '' )
transformers.file_utils.replace_return_docstrings
< source >( output_type = None config_class = None )
Special Properties
class transformers.file_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.
Other Utilities
class transformers._LazyModule
< source >( name module_file import_structure module_spec = None extra_objects = None )
Module class that surfaces all objects but only performs associated imports when the objects are requested.