'''simple docstring'''





def 	lowerCAmelCase_				(					snake_case_       : Tuple			)    ->      List[str]:


     '''simple docstring'''




     if collection == []:
          return []

     # get some information about the collection
     UpperCAmelCase_           =   len(snake_case_			)
     UpperCAmelCase_           =   max(snake_case_			)
     UpperCAmelCase_           =   min(snake_case_			)

     # create the counting array
     UpperCAmelCase_           =   coll_max + 1 - coll_min
     UpperCAmelCase_           =   [0] * counting_arr_length

     # count how much a number appears in the collection
     for number in collection:
          counting_arr[number - coll_min] += 1

     # sum each position with it's predecessors. now, counting_arr[i] tells
     # us how many elements <= i has in the collection
     for i in range(1					,    snake_case_			):
          UpperCAmelCase_           =   counting_arr[i] + counting_arr[i - 1]

     # create the output collection
     UpperCAmelCase_           =   [0] * coll_len

     # place the elements in the output, respecting the original order (stable
     # sort) from end to begin, updating counting_arr
     for i in reversed(range(0					,    snake_case_			)			):
          UpperCAmelCase_           =   collection[i]
          counting_arr[collection[i] - coll_min] -= 1

     return ordered





def 	lowerCAmelCase_				(					snake_case_       : List[Any]			)    ->      Tuple:


     '''simple docstring'''




     return "".join([chr(snake_case_			) for i in counting_sort([ord(snake_case_			) for c in string]			)]			)


if __name__ == "__main__":
    # Test string sort
    assert counting_sort_string('thisisthestring') == "eghhiiinrsssttt"

    SCREAMING_SNAKE_CASE_:     List[Any]  =input('Enter numbers separated by a comma:\n').strip()
    SCREAMING_SNAKE_CASE_:     Union[str, Any]  =[int(item) for item in user_input.split(',')]
    print(counting_sort(unsorted))









'''simple docstring'''






from typing import TYPE_CHECKING

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


A_							: Optional[Any]						 =	{
    """configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaConfig"""],
}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A_							: List[str]						 =	["""LlamaTokenizer"""]

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A_							: Dict						 =	["""LlamaTokenizerFast"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A_							: Optional[int]						 =	[
       """LlamaForCausalLM""",
       """LlamaModel""",
       """LlamaPreTrainedModel""",
       """LlamaForSequenceClassification""",
   ]


if TYPE_CHECKING:
   from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_llama import LlamaTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_llama_fast import LlamaTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
   import sys

   A_							: Any						 =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



