



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase_	       =			{'''configuration_reformer''': ['''REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ReformerConfig''']}

try:
				if not is_sentencepiece_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_	       =			['''ReformerTokenizer''']

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_	       =			['''ReformerTokenizerFast''']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_	       =			[
				    '''REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''ReformerAttention''',
				    '''ReformerForMaskedLM''',
				    '''ReformerForQuestionAnswering''',
				    '''ReformerForSequenceClassification''',
				    '''ReformerLayer''',
				    '''ReformerModel''',
				    '''ReformerModelWithLMHead''',
				    '''ReformerPreTrainedModel''',
				]


if TYPE_CHECKING:
				from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

				try:
								if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_reformer import ReformerTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_reformer_fast import ReformerTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_reformer import (
								    REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    ReformerAttention,
								    ReformerForMaskedLM,
								    ReformerForQuestionAnswering,
								    ReformerForSequenceClassification,
								    ReformerLayer,
								    ReformerModel,
								    ReformerModelWithLMHead,
								    ReformerPreTrainedModel,
								)

else:
				import sys

				lowercase_	       =			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)









import warnings

from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor


lowercase_	       =			logging.get_logger(__name__)






class 						__a (     SCREAMING_SNAKE_CASE				):



	def __init__(						self							:    Optional[Any]				,	*snake_case_							:    List[str]				,	**snake_case_							:    Union[str, Any])->							None:
						warnings.warn(
						    """The class PoolFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
						    """ Please use PoolFormerImageProcessor instead."""				,	snake_case_				,	)
						super().__init__(*snake_case_				,	**snake_case_)




