

'''simple docstring'''
from typing import TYPE_CHECKING

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


lowerCamelCase			:				Any 			=					{
    'configuration_mobilebert': [
        'MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MobileBertConfig',
        'MobileBertOnnxConfig',
    ],
    'tokenization_mobilebert': ['MobileBertTokenizer'],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase			:				int 			=					['MobileBertTokenizerFast']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase			:				Optional[Any] 			=					[
					    'MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'MobileBertForMaskedLM',
					    'MobileBertForMultipleChoice',
					    'MobileBertForNextSentencePrediction',
					    'MobileBertForPreTraining',
					    'MobileBertForQuestionAnswering',
					    'MobileBertForSequenceClassification',
					    'MobileBertForTokenClassification',
					    'MobileBertLayer',
					    'MobileBertModel',
					    'MobileBertPreTrainedModel',
					    'load_tf_weights_in_mobilebert',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase			:				Optional[int] 			=					[
					    'TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'TFMobileBertForMaskedLM',
					    'TFMobileBertForMultipleChoice',
					    'TFMobileBertForNextSentencePrediction',
					    'TFMobileBertForPreTraining',
					    'TFMobileBertForQuestionAnswering',
					    'TFMobileBertForSequenceClassification',
					    'TFMobileBertForTokenClassification',
					    'TFMobileBertMainLayer',
					    'TFMobileBertModel',
					    'TFMobileBertPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_mobilebert import (
					    MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    MobileBertConfig,
					    MobileBertOnnxConfig,
					)
					from .tokenization_mobilebert import MobileBertTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_mobilebert_fast import MobileBertTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_mobilebert import (
										    MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MobileBertForMaskedLM,
										    MobileBertForMultipleChoice,
										    MobileBertForNextSentencePrediction,
										    MobileBertForPreTraining,
										    MobileBertForQuestionAnswering,
										    MobileBertForSequenceClassification,
										    MobileBertForTokenClassification,
										    MobileBertLayer,
										    MobileBertModel,
										    MobileBertPreTrainedModel,
										    load_tf_weights_in_mobilebert,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_mobilebert import (
										    TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFMobileBertForMaskedLM,
										    TFMobileBertForMultipleChoice,
										    TFMobileBertForNextSentencePrediction,
										    TFMobileBertForPreTraining,
										    TFMobileBertForQuestionAnswering,
										    TFMobileBertForSequenceClassification,
										    TFMobileBertForTokenClassification,
										    TFMobileBertMainLayer,
										    TFMobileBertModel,
										    TFMobileBertPreTrainedModel,
										)

else:
					import sys

					lowerCamelCase			:				str 			=					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



'''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig


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

lowerCamelCase			:				Optional[Any] 			=					"T5Config"







class 							A__   (	A__  ):
  A__					=    'mt5'
  A__					=    MTaConfig







class 							A__   (	A__  ):
  A__					=    'mt5'
  A__					=    MTaConfig







class 							A__   (	A__  ):
  A__					=    'mt5'
  A__					=    MTaConfig
