



'''simple docstring'''





import warnings

from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor


A__    :   Dict           =					logging.get_logger(__name__)



class  snake_case__						(    SCREAMING_SNAKE_CASE_				):
 def __init__(   self						:							Optional[int]      ,     *__a						:							int      ,     **__a						:							Dict  )      ->   None:







       '''simple docstring'''
       warnings.warn(
           'The class DeformableDetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
           ' Please use DeformableDetrImageProcessor instead.'      ,     __a      ,     )
       super().__init__(*__a      ,     **__a  )








'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


A__    :   Optional[Any]           =					{
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A__    :   Tuple           =					['''SqueezeBertTokenizerFast''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A__    :   str           =					[
        '''SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''SqueezeBertForMaskedLM''',
        '''SqueezeBertForMultipleChoice''',
        '''SqueezeBertForQuestionAnswering''',
        '''SqueezeBertForSequenceClassification''',
        '''SqueezeBertForTokenClassification''',
        '''SqueezeBertModel''',
        '''SqueezeBertModule''',
        '''SqueezeBertPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_squeezebert import (
        SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
        SqueezeBertConfig,
        SqueezeBertOnnxConfig,
    )
    from .tokenization_squeezebert import SqueezeBertTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_squeezebert import (
            SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            SqueezeBertForMaskedLM,
            SqueezeBertForMultipleChoice,
            SqueezeBertForQuestionAnswering,
            SqueezeBertForSequenceClassification,
            SqueezeBertForTokenClassification,
            SqueezeBertModel,
            SqueezeBertModule,
            SqueezeBertPreTrainedModel,
        )

else:
    import sys

    A__    :   List[Any]           =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



