



"""simple docstring"""






import warnings

from ...utils import logging
from .image_processing_vilt import ViltImageProcessor


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

class 			__SCREAMING_SNAKE_CASE      ( lowerCAmelCase_  ):


					'''simple docstring'''





					def __init__(			self				:    str,    *lowerCamelCase				:    List[str],    **lowerCamelCase				:    Tuple	)->   None:
								warnings.warn(
								    '''The class ViltFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
								    ''' use ViltImageProcessor instead.''',    lowerCamelCase,    )
								super().__init__(*lowerCamelCase,    **lowerCamelCase	)











'''simple docstring'''


from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


_lowerCamelCase					:						str					     =							{
    'configuration_ernie_m': ['ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieMConfig'],
}

try:
				if not is_sentencepiece_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCamelCase					:						List[str]					     =							['ErnieMTokenizer']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCamelCase					:						Union[str, Any]					     =							[
				    'ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'ErnieMForMultipleChoice',
				    'ErnieMForQuestionAnswering',
				    'ErnieMForSequenceClassification',
				    'ErnieMForTokenClassification',
				    'ErnieMModel',
				    'ErnieMPreTrainedModel',
				    'ErnieMForInformationExtraction',
				]


if TYPE_CHECKING:
				from .configuration_ernie_m import ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieMConfig

				try:
								if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_ernie_m import ErnieMTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_ernie_m import (
								    ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST,
								    ErnieMForInformationExtraction,
								    ErnieMForMultipleChoice,
								    ErnieMForQuestionAnswering,
								    ErnieMForSequenceClassification,
								    ErnieMForTokenClassification,
								    ErnieMModel,
								    ErnieMPreTrainedModel,
								)


else:
				import sys

				_lowerCamelCase					:						int					     =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

