bCiP S r SSKrSSKrSSKrSSKrSSKJr SSKJrJ r SSK
J r SSK J
r
Jr SSKJr SS KJrJrJrJr S
S KJr S
S KJrJrJrJ r \R: " \ 5 r \" / S
Q5 r \" \\ 5 r!S\"4S jr# S S\ \"\RH 4 S\\ \"\RH 4 S\%S\\% S\\&\"\"4 S\\ \%\"4 S\\" S\%4S jjr' " S S5 r(SS/r)g) zAutoFeatureExtractor class. N) OrderedDict)OptionalUnion )PretrainedConfig) get_class_from_dynamic_moduleresolve_trust_remote_code)FeatureExtractionMixin) CONFIG_NAMEFEATURE_EXTRACTOR_NAME cached_filelogging )_LazyAutoMapping)CONFIG_MAPPING_NAMES
AutoConfigmodel_type_to_module_name!replace_list_option_in_docstrings)P)z audio-spectrogram-transformerASTFeatureExtractor)beitBeitFeatureExtractor) chinese_clipChineseCLIPFeatureExtractor)clapClapFeatureExtractor)clipCLIPFeatureExtractor)clipsegViTFeatureExtractor)clvpClvpFeatureExtractor)conditional_detr ConditionalDetrFeatureExtractor)convnextConvNextFeatureExtractor)cvtr% )dacDacFeatureExtractor)zdata2vec-audioWav2Vec2FeatureExtractor)zdata2vec-visionr )deformable_detr DeformableDetrFeatureExtractor)deitDeiTFeatureExtractor)detrDetrFeatureExtractor)diaDiaFeatureExtractor)dinatr )z
donut-swinDonutFeatureExtractor)dptDPTFeatureExtractor)encodecEncodecFeatureExtractor)flavaFlavaFeatureExtractor)gemma3n Gemma3nAudioFeatureExtractor)glpnGLPNFeatureExtractor)granite_speech GraniteSpeechFeatureExtractor)groupvitr )hubertr) )imagegptImageGPTFeatureExtractor)kyutai_speech_to_text"KyutaiSpeechToTextFeatureExtractor)
layoutlmv2LayoutLMv2FeatureExtractor)
layoutlmv3LayoutLMv3FeatureExtractor)levitLevitFeatureExtractor)
maskformerMaskFormerFeatureExtractor)mctctMCTCTFeatureExtractor)mimir7 ) mobilenet_v1MobileNetV1FeatureExtractor) mobilenet_v2MobileNetV2FeatureExtractor) mobilevitMobileViTFeatureExtractor) moonshiner) )moshir7 )natr )owlvitOwlViTFeatureExtractor) parakeet_ctcParakeetFeatureExtractor)parakeet_encoderr] ) perceiverPerceiverFeatureExtractor)phi4_multimodal Phi4MultimodalFeatureExtractor)
poolformerPoolFormerFeatureExtractor) pop2pianoPop2PianoFeatureExtractor)regnetr% )resnetr% ) seamless_m4tSeamlessM4TFeatureExtractor)seamless_m4t_v2rj ) segformerSegformerFeatureExtractor)sewr) )zsew-dr) )speech_to_textSpeech2TextFeatureExtractor)speecht5SpeechT5FeatureExtractor) swiftformerr )swinr )swinv2r )ztable-transformerr/ ) timesformerVideoMAEFeatureExtractor)tvltTvltFeatureExtractor) unispeechr) )z
unispeech-satr) )univnetUnivNetFeatureExtractor)vanr% )videomaerw )viltViltFeatureExtractor)vitr )vit_maer )vit_msnr )wav2vec2r) )z
wav2vec2-bertr) )zwav2vec2-conformerr) )wavlmr) )whisperWhisperFeatureExtractor)xclipr )xcodecr( )yolosYolosFeatureExtractor
class_namec [ R 5 H= u pX; d M [ U5 n[ R " SU 3S5 n [ X05 s $ [ R R 5 H n[ USS 5 U :X d M Us $ [ R " S5 n[ XP5 ( a [ XP5 $ g ! [ a M f = f)N.ztransformers.models__name__ transformers) FEATURE_EXTRACTOR_MAPPING_NAMESitemsr importlib
import_modulegetattrAttributeErrorFEATURE_EXTRACTOR_MAPPING_extra_contentvalueshasattr)r module_name
extractorsmodule extractor main_modules j/home/james-whalen/.local/lib/python3.13/site-packages/transformers/models/auto/feature_extraction_auto.py!feature_extractor_class_from_namer s #B#H#H#J #3K@K ,,q
->@UVF
v22
$K /==DDF 9j$ /: = G )).9K{''{// "
s
C
CC pretrained_model_name_or_path cache_dirforce_downloadresume_downloadproxiestokenrevisionlocal_files_onlyc \ UR SS5 n U b+ [ R " S[ 5 Ub [ S5 eU n[ U [ UUUUUUUSSSS9 n
U
c [ R S5 0 $ [ U
SS 9 n [ R " U 5 sSSS5 $ ! , ( d f g= f)
ar
Loads the tokenizer configuration from a pretrained model tokenizer configuration.
Args:
pretrained_model_name_or_path (`str` or `os.PathLike`):
This can be either:
- a string, the *model id* of a pretrained model configuration hosted inside a model repo on
huggingface.co.
- a path to a *directory* containing a configuration file saved using the
[`~PreTrainedTokenizer.save_pretrained`] method, e.g., `./my_model_directory/`.
cache_dir (`str` or `os.PathLike`, *optional*):
Path to a directory in which a downloaded pretrained model configuration should be cached if the standard
cache should not be used.
force_download (`bool`, *optional*, defaults to `False`):
Whether or not to force to (re-)download the configuration files and override the cached versions if they
exist.
resume_download:
Deprecated and ignored. All downloads are now resumed by default when possible.
Will be removed in v5 of Transformers.
proxies (`dict[str, str]`, *optional*):
A dictionary of proxy servers to use by protocol or endpoint, e.g., `{'http': 'foo.bar:3128',
'http://hostname': 'foo.bar:4012'}.` The proxies are used on each request.
token (`str` or *bool*, *optional*):
The token to use as HTTP bearer authorization for remote files. If `True`, will use the token generated
when running `hf auth login` (stored in `~/.huggingface`).
revision (`str`, *optional*, defaults to `"main"`):
The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
git-based system for storing models and other artifacts on huggingface.co, so `revision` can be any
identifier allowed by git.
local_files_only (`bool`, *optional*, defaults to `False`):
If `True`, will only try to load the tokenizer configuration from local files.
Passing `token=True` is required when you want to use a private model.
Returns:
`Dict`: The configuration of the tokenizer.
Examples:
```python
# Download configuration from huggingface.co and cache.
tokenizer_config = get_tokenizer_config("google-bert/bert-base-uncased")
# This model does not have a tokenizer config so the result will be an empty dict.
tokenizer_config = get_tokenizer_config("FacebookAI/xlm-roberta-base")
# Save a pretrained tokenizer locally and you can reload its config
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-cased")
tokenizer.save_pretrained("tokenizer-test")
tokenizer_config = get_tokenizer_config("tokenizer-test")
```use_auth_tokenNrThe `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.V`token` and `use_auth_token` are both specified. Please set only the argument `token`.F)
r r r r r r r _raise_exceptions_for_gated_repo%_raise_exceptions_for_missing_entries'_raise_exceptions_for_connection_errorszdCould not locate the feature extractor configuration file, will try to use the model config instead.zutf-8)encoding) popwarningswarn
FutureWarning
ValueErrorr
r loggerinfoopenjsonload) r r r r r r r r kwargsr resolved_config_filereaders r get_feature_extractor_configr s J ZZ 0$7N!
A
uv v &% %'))..305
# r
"W 5yy
6 5 5s =B
B+c X \ rS rSrSrS r\\" \5 S 5 5 r \
SS j5 r Sr g) AutoFeatureExtractor a
This is a generic feature extractor class that will be instantiated as one of the feature extractor classes of the
library when created with the [`AutoFeatureExtractor.from_pretrained`] class method.
This class cannot be instantiated directly using `__init__()` (throws an error).
c [ S5 e)NzAutoFeatureExtractor is designed to be instantiated using the `AutoFeatureExtractor.from_pretrained(pretrained_model_name_or_path)` method.)OSError)selfs r __init__ AutoFeatureExtractor.__init__ s
f
c UR SS5 nUb< [ R " S[ 5 UR S5 b [ S5 eX2S' UR SS5 nUR SS5 nSUS ' [ R " U40 UD6u pgUR S
S5 nSn S UR S 0 5 ; a US S n Ucn U ck [ U[ 5 ( d [ R " U4SU0UD6n[ US
S5 n[ US 5 ( a S UR ; a UR S n Ub [ U5 nU SLn
USL=( d [! U5 [" ; n U
( a* S
U ; a U R% S
5 S n OSn [' XQXU 5 nU
( aH U( aA [) X40 UD6nUR SS5 nUR+ 5 UR, " U40 UD6$ Ub UR, " U40 UD6$ [! U5 [" ; a% [" [! U5 nUR, " U40 UD6$ [ SU S[. S[0 S[0 SSR3 S [4 5 5 3
5 e)a
Instantiate one of the feature extractor classes of the library from a pretrained model vocabulary.
The feature extractor class to instantiate is selected based on the `model_type` property of the config object
(either passed as an argument or loaded from `pretrained_model_name_or_path` if possible), or when it's
missing, by falling back to using pattern matching on `pretrained_model_name_or_path`:
List options
Params:
pretrained_model_name_or_path (`str` or `os.PathLike`):
This can be either:
- a string, the *model id* of a pretrained feature_extractor hosted inside a model repo on
huggingface.co.
- a path to a *directory* containing a feature extractor file saved using the
[`~feature_extraction_utils.FeatureExtractionMixin.save_pretrained`] method, e.g.,
`./my_model_directory/`.
- a path or url to a saved feature extractor JSON *file*, e.g.,
`./my_model_directory/preprocessor_config.json`.
cache_dir (`str` or `os.PathLike`, *optional*):
Path to a directory in which a downloaded pretrained model feature extractor should be cached if the
standard cache should not be used.
force_download (`bool`, *optional*, defaults to `False`):
Whether or not to force to (re-)download the feature extractor files and override the cached versions
if they exist.
resume_download:
Deprecated and ignored. All downloads are now resumed by default when possible.
Will be removed in v5 of Transformers.
proxies (`dict[str, str]`, *optional*):
A dictionary of proxy servers to use by protocol or endpoint, e.g., `{'http': 'foo.bar:3128',
'http://hostname': 'foo.bar:4012'}.` The proxies are used on each request.
token (`str` or *bool*, *optional*):
The token to use as HTTP bearer authorization for remote files. If `True`, will use the token generated
when running `hf auth login` (stored in `~/.huggingface`).
revision (`str`, *optional*, defaults to `"main"`):
The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
git-based system for storing models and other artifacts on huggingface.co, so `revision` can be any
identifier allowed by git.
return_unused_kwargs (`bool`, *optional*, defaults to `False`):
If `False`, then this function returns just the final feature extractor object. If `True`, then this
functions returns a `Tuple(feature_extractor, unused_kwargs)` where *unused_kwargs* is a dictionary
consisting of the key/value pairs whose keys are not feature extractor attributes: i.e., the part of
`kwargs` which has not been used to update `feature_extractor` and is otherwise ignored.
trust_remote_code (`bool`, *optional*, defaults to `False`):
Whether or not to allow for custom models defined on the Hub in their own modeling files. This option
should only be set to `True` for repositories you trust and in which you have read the code, as it will
execute code present on the Hub on your local machine.
kwargs (`dict[str, Any]`, *optional*):
The values in kwargs of any keys which are feature extractor attributes will be used to override the
loaded values. Behavior concerning key/value pairs whose keys are *not* feature extractor attributes is
controlled by the `return_unused_kwargs` keyword parameter.
Passing `token=True` is required when you want to use a private model.
Examples:
```python
>>> from transformers import AutoFeatureExtractor
>>> # Download feature extractor from huggingface.co and cache.
>>> feature_extractor = AutoFeatureExtractor.from_pretrained("facebook/wav2vec2-base-960h")
>>> # If feature extractor files are in a directory (e.g. feature extractor was saved using *save_pretrained('./test/saved_model/')*)
>>> # feature_extractor = AutoFeatureExtractor.from_pretrained("./test/saved_model/")
```r Nr r r configtrust_remote_codeT
_from_autofeature_extractor_typer auto_mapz--r
code_revisionz"Unrecognized feature extractor in z4. Should have a `feature_extractor_type` key in its z of z3, or one of the following `model_type` keys in its z: z, c 3 $ # U H ov M g 7f)N ).0cs r 7AutoFeatureExtractor.from_pretrained.. s @lLkqLks )r r r r getr r
get_feature_extractor_dict
isinstancer r from_pretrainedr r r r typer splitr r register_for_auto_class from_dictr r joinr )
clsr r r r r config_dict_feature_extractor_classfeature_extractor_auto_maphas_remote_codehas_local_code
upstream_repos
r r $AutoFeatureExtractor.from_pretrained
s R $4d; % MM E
zz'". l -7OHd+ "JJ':D A #| /JJKhslrs "-//2JD"Q %)" ![__Z%D D)4Z)@AW)X & # */I/Q f&677#331EVZ` '.f6NPT&U #vz**/E /X-3__=S-T* " .&GH_&` #4D@0<iV Pi@i 11 : @ @ Fq I
$
9!.cp! 0&C*'MS' #
?D1A # ; ; =*44[KFK K
$
0*44[KFK K
&\ 6
6&?V &M #*44[KFK K01N0O P33I2J${m \((3}Btyy@lLk@l7l6m
o
r c , [ R XUS9 g)a
Register a new feature extractor for this class.
Args:
config_class ([`PretrainedConfig`]):
The configuration corresponding to the model to register.
feature_extractor_class ([`FeatureExtractorMixin`]): The feature extractor to register.
)exist_okN)r register) config_classr r s r r AutoFeatureExtractor.register s "**<[c*dr r N)F)
r
__module__ __qualname____firstlineno____doc__r classmethodr r r staticmethodr __static_attributes__r r r r r sH
&'FGH
H H
T e er r r )NFNNNNF)*r r r osr collectionsr typingr r configuration_utilsr dynamic_module_utilsr r feature_extraction_utilsr
utilsr r r
r auto_factoryr configuration_autor r r r
get_loggerr r r r strr PathLikebooldictr r __all__r r r r sN " # " 4 \ > N N *
H %"-QS# j --ACb c # 4 48 &*(,(, " "d!#(bkk)9#:d!c2;; ./0d! d! d^ d!
d38n
% d! E$)$ %
d! smd! d!Nde deN '(>
?r