




"""simple docstring"""





from typing import TYPE_CHECKING

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


A				=							{
    """configuration_mobilebert""": [
        """MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """MobileBertConfig""",
        """MobileBertOnnxConfig""",
    ],
    """tokenization_mobilebert""": ["""MobileBertTokenizer"""],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A				=							["""MobileBertTokenizerFast"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A				=							[
					    """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:
					A				=							[
					    """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

					A				=							_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





_UpperCAmelCase						:  Any									=			6_5521





def    __lowerCamelCase      (					UpperCamelCase__ ):







							'''simple docstring'''






							snake_case_     							=       1
							snake_case_     							=       0
							for plain_chr in plain_text:
														snake_case_     							=       (a + ord(UpperCamelCase__ )) % MOD_ADLER
														snake_case_     							=       (b + a) % MOD_ADLER
							return (b << 16) | a




