



'''simple docstring'''






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





       '''simple docstring'''


       if collection == []:
              return []

       # get some information about the collection
       _UpperCAmelCase  :						str			     = len(lowerCAmelCase_		)
       _UpperCAmelCase  :						int			     = max(lowerCAmelCase_		)
       _UpperCAmelCase  :						Union[str, Any]			     = min(lowerCAmelCase_		)

       # create the counting array
       _UpperCAmelCase  :						Tuple			     = coll_max + 1 - coll_min
       _UpperCAmelCase  :						Union[str, Any]			     = [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       ,   lowerCAmelCase_		):
              _UpperCAmelCase  :						Optional[Any]			     = counting_arr[i] + counting_arr[i - 1]

       # create the output collection
       _UpperCAmelCase  :						Union[str, Any]			     = [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       ,   lowerCAmelCase_		)		):
              _UpperCAmelCase  :						List[str]			     = collection[i]
              counting_arr[collection[i] - coll_min] -= 1

       return ordered




def     snake_case_					(     lowerCAmelCase_		)->		Dict:





       '''simple docstring'''


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


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

   A_							: Dict						 =	input("""Enter numbers separated by a comma:\n""").strip()
   A_							: 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__)



