def       __lowerCamelCase		(						lowerCAmelCase__	):
       barcode //= 1_0  # exclude the last digit
       lowerCAmelCase__     	=					False
       lowerCAmelCase__     	=					0

       # extract and check each digit
       while barcode != 0:
              lowerCAmelCase__     	=					1 if checker else 3
              s += mult * (barcode % 1_0)
              barcode //= 1_0
              lowerCAmelCase__     	=					not checker

       return (1_0 - (s % 1_0)) % 1_0






def       __lowerCamelCase		(						lowerCAmelCase__	):
       return len(str(lowerCAmelCase__	)	) == 1_3 and get_check_digit(lowerCAmelCase__	) == barcode % 1_0






def       __lowerCamelCase		(						lowerCAmelCase__	):
       if str(lowerCAmelCase__	).isalpha():
              lowerCAmelCase__     	=					F"""Barcode '{barcode}' has alphabetic characters."""
              raise ValueError(lowerCAmelCase__	)
       elif int(lowerCAmelCase__	) < 0:
              raise ValueError('The entered barcode has a negative value. Try again.'	)
       else:
              return int(lowerCAmelCase__	)


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    lowerCAmelCase__							= get_barcode(input('Barcode: ').strip())

    if is_valid(barcode):
        print(F'\'{barcode}\' is a valid barcode.')
    else:
        print(F'\'{barcode}\' is NOT a valid barcode.')

from typing import TYPE_CHECKING

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


lowerCAmelCase__							= {
    'configuration_deberta_v2': ['DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DebertaV2Config', 'DebertaV2OnnxConfig'],
    'tokenization_deberta_v2': ['DebertaV2Tokenizer'],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__							= ['DebertaV2TokenizerFast']

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__							= [
        'TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST',
        'TFDebertaV2ForMaskedLM',
        'TFDebertaV2ForQuestionAnswering',
        'TFDebertaV2ForSequenceClassification',
        'TFDebertaV2ForTokenClassification',
        'TFDebertaV2Model',
        'TFDebertaV2PreTrainedModel',
    ]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase__							= [
        'DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST',
        'DebertaV2ForMaskedLM',
        'DebertaV2ForMultipleChoice',
        'DebertaV2ForQuestionAnswering',
        'DebertaV2ForSequenceClassification',
        'DebertaV2ForTokenClassification',
        'DebertaV2Model',
        'DebertaV2PreTrainedModel',
    ]


if TYPE_CHECKING:
    from .configuration_deberta_va import (
        DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
        DebertaVaConfig,
        DebertaVaOnnxConfig,
    )
    from .tokenization_deberta_va import DebertaVaTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_deberta_va_fast import DebertaVaTokenizerFast

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_deberta_va import (
            TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFDebertaVaForMaskedLM,
            TFDebertaVaForQuestionAnswering,
            TFDebertaVaForSequenceClassification,
            TFDebertaVaForTokenClassification,
            TFDebertaVaModel,
            TFDebertaVaPreTrainedModel,
        )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_deberta_va import (
            DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
            DebertaVaForMaskedLM,
            DebertaVaForMultipleChoice,
            DebertaVaForQuestionAnswering,
            DebertaVaForSequenceClassification,
            DebertaVaForTokenClassification,
            DebertaVaModel,
            DebertaVaPreTrainedModel,
        )

else:
    import sys

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