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

< >

( 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

< >

( 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

< >

( 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.add_start_docstrings

< >

( *docstr )

transformers.file_utils.add_start_docstrings_to_model_forward

< >

( *docstr )

transformers.add_end_docstrings

< >

( *docstr )

transformers.file_utils.add_code_sample_docstrings

< >

( *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

< >

( output_type = None config_class = None )

Special Properties

class transformers.file_utils.cached_property

< >

( 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

< >

( 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.