



def   SCREAMING_SNAKE_CASE_       (  _snake_case  :list							)     ->    list:

			for insert_index, insert_value in enumerate(collection[1:]							):
						_A						     =					insert_index
						while insert_index >= 0 and insert_value < collection[insert_index]:
									_A						     =					collection[insert_index]
									insert_index -= 1
						if insert_index != temp_index:
									_A						     =					insert_value
			return collection


if __name__ == "__main__":
			from doctest import testmod

			testmod()

			UpperCAmelCase_		   =				input("""Enter numbers separated by a comma:\n""").strip()
			UpperCAmelCase_		   =				[int(item) for item in user_input.split(""",""")]
			print(f'{insertion_sort(unsorted) = }')








from typing import TYPE_CHECKING

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


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

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

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

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



