General Utilities

This page lists all of Transformers general utility functions that are found in the file utils.py.

Most of those are only useful if you are studying the general code in the library.

Enums and namedtuples

class transformers.utils.ExplicitEnum

< >

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

Enum with more explicit error message for missing values.

class transformers.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.utils.add_start_docstrings_to_model_forward

< >

( *docstr )

transformers.add_end_docstrings

< >

( *docstr )

transformers.utils.add_code_sample_docstrings

< >

( *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 = '' expected_loss = '' )

transformers.utils.replace_return_docstrings

< >

( output_type = None config_class = None )

Special Properties

class transformers.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.