



def   SCREAMING_SNAKE_CASE_       (  _snake_case  :Optional[int]							)     ->    List[str]:
   _A						     =					len(_snake_case							)
   for i in range(length - 1							):
      _A						     =					False
      for j in range(length - 1 - i							):
         if collection[j] > collection[j + 1]:
            _A						     =					True
            _A     ,						_A						     =					collection[j + 1], collection[j]
      if not swapped:
         break  # Stop iteration if the collection is sorted.
   return collection


if __name__ == "__main__":
   import doctest
   import time

   doctest.testmod()

   UpperCAmelCase_		   =				input("""Enter numbers separated by a comma:""").strip()
   UpperCAmelCase_		   =				[int(item) for item in user_input.split(""",""")]
   UpperCAmelCase_		   =				time.process_time()
   print(*bubble_sort(unsorted), sep=""",""")
   print(f'Processing time: {(time.process_time() - start)%1E9 + 7}')








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__)



