




from typing import TYPE_CHECKING

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


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

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

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

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










def 			_a   (		SCREAMING_SNAKE_CASE_							:       list[int]  ):
					__lowerCAmelCase            = len(SCREAMING_SNAKE_CASE_  )
					for i in range(SCREAMING_SNAKE_CASE_  ):
										for j in range(i + 1   ,   SCREAMING_SNAKE_CASE_  ):
															if numbers[j] < numbers[i]:
																				__lowerCAmelCase     ,							__lowerCAmelCase            = numbers[j], numbers[i]
					return numbers


if __name__ == "__main__":
					UpperCamelCase__					    =    input("""Enter numbers separated by a comma:\n""").strip()
					UpperCamelCase__					    =    [int(item) for item in user_input.split(""",""")]
					print(exchange_sort(unsorted))




