



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE__   			=   {
    '''configuration_electra''': ['''ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ElectraConfig''', '''ElectraOnnxConfig'''],
    '''tokenization_electra''': ['''ElectraTokenizer'''],
}

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

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__   			=   [
							    '''ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''ElectraForCausalLM''',
							    '''ElectraForMaskedLM''',
							    '''ElectraForMultipleChoice''',
							    '''ElectraForPreTraining''',
							    '''ElectraForQuestionAnswering''',
							    '''ElectraForSequenceClassification''',
							    '''ElectraForTokenClassification''',
							    '''ElectraModel''',
							    '''ElectraPreTrainedModel''',
							    '''load_tf_weights_in_electra''',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__   			=   [
							    '''TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''TFElectraForMaskedLM''',
							    '''TFElectraForMultipleChoice''',
							    '''TFElectraForPreTraining''',
							    '''TFElectraForQuestionAnswering''',
							    '''TFElectraForSequenceClassification''',
							    '''TFElectraForTokenClassification''',
							    '''TFElectraModel''',
							    '''TFElectraPreTrainedModel''',
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__   			=   [
							    '''FlaxElectraForCausalLM''',
							    '''FlaxElectraForMaskedLM''',
							    '''FlaxElectraForMultipleChoice''',
							    '''FlaxElectraForPreTraining''',
							    '''FlaxElectraForQuestionAnswering''',
							    '''FlaxElectraForSequenceClassification''',
							    '''FlaxElectraForTokenClassification''',
							    '''FlaxElectraModel''',
							    '''FlaxElectraPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_electra import ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP, ElectraConfig, ElectraOnnxConfig
							from .tokenization_electra import ElectraTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_electra_fast import ElectraTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_electra import (
														    ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ElectraForCausalLM,
														    ElectraForMaskedLM,
														    ElectraForMultipleChoice,
														    ElectraForPreTraining,
														    ElectraForQuestionAnswering,
														    ElectraForSequenceClassification,
														    ElectraForTokenClassification,
														    ElectraModel,
														    ElectraPreTrainedModel,
														    load_tf_weights_in_electra,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_electra import (
														    TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFElectraForMaskedLM,
														    TFElectraForMultipleChoice,
														    TFElectraForPreTraining,
														    TFElectraForQuestionAnswering,
														    TFElectraForSequenceClassification,
														    TFElectraForTokenClassification,
														    TFElectraModel,
														    TFElectraPreTrainedModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_electra import (
														    FlaxElectraForCausalLM,
														    FlaxElectraForMaskedLM,
														    FlaxElectraForMultipleChoice,
														    FlaxElectraForPreTraining,
														    FlaxElectraForQuestionAnswering,
														    FlaxElectraForSequenceClassification,
														    FlaxElectraForTokenClassification,
														    FlaxElectraModel,
														    FlaxElectraPreTrainedModel,
														)

else:
							import sys

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









import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


SCREAMING_SNAKE_CASE__   			=   logging.get_logger(__name__)


class   __lowerCAmelCase  (		UpperCAmelCase_   ):
					"""simple docstring"""






					def __init__(  self       :							Dict					,       *_snake_case       :							int					,       **_snake_case       :							Optional[int]       ):






								"""simple docstring"""


								warnings.warn(
								    'The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
								    ' use CLIPImageProcessor instead.'					,       _snake_case					,       )
								super().__init__(*_snake_case					,       **_snake_case       )




