





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







  """simple docstring"""





  if collection == []:
    return []

  # get some information about the collection
  lowerCamelCase__:      List[Any]			  =len(__a		)
  lowerCamelCase__:      List[str]			  =max(__a		)
  lowerCamelCase__:      Dict			  =min(__a		)

  # create the counting array
  lowerCamelCase__:      Tuple			  =coll_max + 1 - coll_min
  lowerCamelCase__:      Optional[int]			  =[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	,    __a		):
    lowerCamelCase__:      int			  =counting_arr[i] + counting_arr[i - 1]

  # create the output collection
  lowerCamelCase__:      Dict			  =[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	,    __a		)		):
    lowerCamelCase__:      int			  =collection[i]
    counting_arr[collection[i] - coll_min] -= 1

  return ordered





def      lowerCAmelCase_ (       __a		)     ->		str:







  """simple docstring"""





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


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

     __A									=				input("Enter numbers separated by a comma:\n").strip()
     __A									=				[int(item) for item in user_input.split(",")]
     print(counting_sort(unsorted))





from typing import TYPE_CHECKING

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


snake_case							:       str     			=      {
    '''configuration_rag''': ['''RagConfig'''],
    '''retrieval_rag''': ['''RagRetriever'''],
    '''tokenization_rag''': ['''RagTokenizer'''],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						snake_case							:       Any     			=      [
						    '''RagModel''',
						    '''RagPreTrainedModel''',
						    '''RagSequenceForGeneration''',
						    '''RagTokenForGeneration''',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						snake_case							:       Optional[int]     			=      [
						    '''TFRagModel''',
						    '''TFRagPreTrainedModel''',
						    '''TFRagSequenceForGeneration''',
						    '''TFRagTokenForGeneration''',
						]


if TYPE_CHECKING:
						from .configuration_rag import RagConfig
						from .retrieval_rag import RagRetriever
						from .tokenization_rag import RagTokenizer

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_rag import (
												    TFRagModel,
												    TFRagPreTrainedModel,
												    TFRagSequenceForGeneration,
												    TFRagTokenForGeneration,
												)

else:
						import sys

						snake_case							:       int     			=      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




