
"""simple docstring"""





from typing import TYPE_CHECKING

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


_a		       =							{
    'configuration_distilbert': [
        'DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'DistilBertConfig',
        'DistilBertOnnxConfig',
    ],
    'tokenization_distilbert': ['DistilBertTokenizer'],
}

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

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _a		       =							[
        'DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
        'DistilBertForMaskedLM',
        'DistilBertForMultipleChoice',
        'DistilBertForQuestionAnswering',
        'DistilBertForSequenceClassification',
        'DistilBertForTokenClassification',
        'DistilBertModel',
        'DistilBertPreTrainedModel',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _a		       =							[
        'TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
        'TFDistilBertForMaskedLM',
        'TFDistilBertForMultipleChoice',
        'TFDistilBertForQuestionAnswering',
        'TFDistilBertForSequenceClassification',
        'TFDistilBertForTokenClassification',
        'TFDistilBertMainLayer',
        'TFDistilBertModel',
        'TFDistilBertPreTrainedModel',
    ]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _a		       =							[
        'FlaxDistilBertForMaskedLM',
        'FlaxDistilBertForMultipleChoice',
        'FlaxDistilBertForQuestionAnswering',
        'FlaxDistilBertForSequenceClassification',
        'FlaxDistilBertForTokenClassification',
        'FlaxDistilBertModel',
        'FlaxDistilBertPreTrainedModel',
    ]


if TYPE_CHECKING:
    from .configuration_distilbert import (
        DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
        DistilBertConfig,
        DistilBertOnnxConfig,
    )
    from .tokenization_distilbert import DistilBertTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_distilbert_fast import DistilBertTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_distilbert import (
            DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            DistilBertForMaskedLM,
            DistilBertForMultipleChoice,
            DistilBertForQuestionAnswering,
            DistilBertForSequenceClassification,
            DistilBertForTokenClassification,
            DistilBertModel,
            DistilBertPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_distilbert import (
            TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFDistilBertForMaskedLM,
            TFDistilBertForMultipleChoice,
            TFDistilBertForQuestionAnswering,
            TFDistilBertForSequenceClassification,
            TFDistilBertForTokenClassification,
            TFDistilBertMainLayer,
            TFDistilBertModel,
            TFDistilBertPreTrainedModel,
        )

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_distilbert import (
            FlaxDistilBertForMaskedLM,
            FlaxDistilBertForMultipleChoice,
            FlaxDistilBertForQuestionAnswering,
            FlaxDistilBertForSequenceClassification,
            FlaxDistilBertForTokenClassification,
            FlaxDistilBertModel,
            FlaxDistilBertPreTrainedModel,
        )

else:
    import sys

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




import math






def    lowerCamelCase__				(				__lowerCAmelCase  :  int				):




			"""simple docstring"""


			lowerCAmelCase_						=	0
			lowerCAmelCase_						=	0
			while num > 0:
						lowerCAmelCase_						=	num % 8
						lowerCAmelCase_						=	octal + (remainder * math.floor(math.pow(10    ,							__lowerCAmelCase				)				))
						counter += 1
						lowerCAmelCase_						=	math.floor(num / 8				)  # basically /= 8 without remainder if any
						# This formatting removes trailing '.0' from `octal`.
			return F"""0o{int(__lowerCAmelCase				)}"""






def    lowerCamelCase__				(				):




			"""simple docstring"""


			print("\n2 in octal is:"				)
			print(decimal_to_octal(2				)				)  # = 2
			print("\n8 in octal is:"				)
			print(decimal_to_octal(8				)				)  # = 10
			print("\n65 in octal is:"				)
			print(decimal_to_octal(65				)				)  # = 101
			print("\n216 in octal is:"				)
			print(decimal_to_octal(216				)				)  # = 330
			print("\n512 in octal is:"				)
			print(decimal_to_octal(512				)				)  # = 1000
			print("\n"				)


if __name__ == "__main__":
			main()



