

def 						SCREAMING_SNAKE_CASE__ (							_UpperCAmelCase,					_UpperCAmelCase )    ->       List[Any]:



    '''simple docstring'''






    while second != 0:
        lowerCAmelCase :	Optional[Any]				=					first & second
        first ^= second
        lowerCAmelCase :	List[Any]				=					c << 1
    return first


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 __A      :   Any          =	int(input('''Enter the first number: ''').strip())
 __A      :   Optional[Any]          =	int(input('''Enter the second number: ''').strip())
 print(F'{add(first, second) = }')







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__)



