
from __future__ import annotations






def        lowerCamelCase__    (    __lowerCAmelCase  :  Union[str, Any]   ,							__lowerCAmelCase  :  str    ):




			"""simple docstring"""


			lowerCAmelCase_      =     0
			lowerCAmelCase_      =     len(__lowerCAmelCase    ) - 1
			while left <= right:
						lowerCAmelCase_      =     (left + right) // 2
						if left == right:
									if sorted_list[middle] < item:
												lowerCAmelCase_      =     middle + 1
									break
						elif sorted_list[middle] < item:
									lowerCAmelCase_      =     middle + 1
						else:
									lowerCAmelCase_      =     middle - 1
			sorted_list.insert(__lowerCAmelCase   ,							__lowerCAmelCase    )
			return sorted_list






def        lowerCamelCase__    (    __lowerCAmelCase  :  List[Any]   ,							__lowerCAmelCase  :  str    ):




			"""simple docstring"""


			lowerCAmelCase_      =     []
			while left and right:
						if left[0][0] < right[0][0]:
									result.append(left.pop(0    )    )
						else:
									result.append(right.pop(0    )    )
			return result + left + right






def        lowerCamelCase__    (    __lowerCAmelCase  :  Any    ):




			"""simple docstring"""


			lowerCAmelCase_      =     len(__lowerCAmelCase    )
			if length <= 1:
						return list_ad
			lowerCAmelCase_      =     length // 2
			return merge(sortlist_ad(list_ad[:middle]    )   ,							sortlist_ad(list_ad[middle:]    )    )






def        lowerCamelCase__    (    __lowerCAmelCase  :  list[int]    ):




			"""simple docstring"""


			if len(__lowerCAmelCase    ) <= 1:
						return collection
			lowerCAmelCase_      =     []
			lowerCAmelCase_      =     False
			for i in range(0   ,							len(__lowerCAmelCase    )   ,							2    ):
						if i == len(__lowerCAmelCase    ) - 1:
									lowerCAmelCase_      =     True
						else:
									if collection[i] < collection[i + 1]:
												two_paired_list.append([collection[i], collection[i + 1]]    )
									else:
												two_paired_list.append([collection[i + 1], collection[i]]    )
			lowerCAmelCase_      =     sortlist_ad(__lowerCAmelCase    )
			lowerCAmelCase_      =     [i[0] for i in sorted_list_ad]
			result.append(sorted_list_ad[-1][1]    )
			if has_last_odd_item:
						lowerCAmelCase_      =     collection[-1]
						lowerCAmelCase_      =     binary_search_insertion(__lowerCAmelCase   ,							__lowerCAmelCase    )
			lowerCAmelCase_      =     False
			for i in range(len(__lowerCAmelCase    ) - 1    ):
						if result[i] == collection[-1] and has_last_odd_item:
									lowerCAmelCase_      =     True
						lowerCAmelCase_      =     sorted_list_ad[i][1]
						# If last_odd_item is inserted before the item's index,
						# you should forward index one more.
						if is_last_odd_item_inserted_before_this_index:
									lowerCAmelCase_      =     result[: i + 2] + binary_search_insertion(result[i + 2 :]   ,							__lowerCAmelCase    )
						else:
									lowerCAmelCase_      =     result[: i + 1] + binary_search_insertion(result[i + 1 :]   ,							__lowerCAmelCase    )

			return result


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





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


_A       =					{
    "configuration_xlm_prophetnet": ["XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMProphetNetConfig"],
}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A       =					["XLMProphetNetTokenizer"]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A       =					[
			    "XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "XLMProphetNetDecoder",
			    "XLMProphetNetEncoder",
			    "XLMProphetNetForCausalLM",
			    "XLMProphetNetForConditionalGeneration",
			    "XLMProphetNetModel",
			    "XLMProphetNetPreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_xlm_prophetnet import (
						    XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
						    XLMProphetNetDecoder,
						    XLMProphetNetEncoder,
						    XLMProphetNetForCausalLM,
						    XLMProphetNetForConditionalGeneration,
						    XLMProphetNetModel,
						    XLMProphetNetPreTrainedModel,
						)

else:
			import sys

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



