





def 					SCREAMING_SNAKE_CASE__				(							UpperCamelCase__:				list     ):
		SCREAMING_SNAKE_CASE__								=   len(UpperCamelCase__     )
		for i in range(1       , UpperCamelCase__     ):
				SCREAMING_SNAKE_CASE__								=   collection[i]
				SCREAMING_SNAKE_CASE__								=   0
				SCREAMING_SNAKE_CASE__								=   i - 1

				while low <= high:
						SCREAMING_SNAKE_CASE__								=   (low + high) // 2
						if val < collection[mid]:
								SCREAMING_SNAKE_CASE__								=   mid - 1
						else:
								SCREAMING_SNAKE_CASE__								=   mid + 1
				for j in range(UpperCamelCase__       , UpperCamelCase__       , -1     ):
						SCREAMING_SNAKE_CASE__								=   collection[j - 1]
				SCREAMING_SNAKE_CASE__								=   val
		return collection


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

"""simple docstring"""



from typing import TYPE_CHECKING

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


UpperCamelCase__          =	{
    'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase__          =	[
        'MEGA_PRETRAINED_MODEL_ARCHIVE_LIST',
        'MegaForCausalLM',
        'MegaForMaskedLM',
        'MegaForMultipleChoice',
        'MegaForQuestionAnswering',
        'MegaForSequenceClassification',
        'MegaForTokenClassification',
        'MegaModel',
        'MegaPreTrainedModel',
    ]

if TYPE_CHECKING:
    from .configuration_mega import MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP, MegaConfig, MegaOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mega import (
            MEGA_PRETRAINED_MODEL_ARCHIVE_LIST,
            MegaForCausalLM,
            MegaForMaskedLM,
            MegaForMultipleChoice,
            MegaForQuestionAnswering,
            MegaForSequenceClassification,
            MegaForTokenClassification,
            MegaModel,
            MegaPreTrainedModel,
        )

else:
    import sys

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

