





from typing import TYPE_CHECKING

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


__lowerCamelCase			:	Optional[Any]					    =	{
    """configuration_ernie""": ["""ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ErnieConfig""", """ErnieOnnxConfig"""],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase			:	int					    =	[
        """ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """ErnieForCausalLM""",
        """ErnieForMaskedLM""",
        """ErnieForMultipleChoice""",
        """ErnieForNextSentencePrediction""",
        """ErnieForPreTraining""",
        """ErnieForQuestionAnswering""",
        """ErnieForSequenceClassification""",
        """ErnieForTokenClassification""",
        """ErnieModel""",
        """ErniePreTrainedModel""",
    ]

if TYPE_CHECKING:
    from .configuration_ernie import ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieConfig, ErnieOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_ernie import (
            ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST,
            ErnieForCausalLM,
            ErnieForMaskedLM,
            ErnieForMultipleChoice,
            ErnieForNextSentencePrediction,
            ErnieForPreTraining,
            ErnieForQuestionAnswering,
            ErnieForSequenceClassification,
            ErnieForTokenClassification,
            ErnieModel,
            ErniePreTrainedModel,
        )

else:
    import sys

    __lowerCamelCase			:	Tuple					    =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)







import warnings

from ...utils import logging
from .image_processing_beit import BeitImageProcessor


__lowerCamelCase			:	Optional[Any]					    =	logging.get_logger(__name__)



class    A__  (			__snake_case     ):





      def __init__(					self			,				*A_			,				**A_  ):
       '''simple docstring'''




       warnings.warn(
           "The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
           " use BeitImageProcessor instead."			,				A_			,				)
       super().__init__(*A_			,				**A_  )
