





from typing import TYPE_CHECKING

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


_snake_case  :    List[Any]						    =  {
    'configuration_ctrl': ['CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CTRLConfig'],
    'tokenization_ctrl': ['CTRLTokenizer'],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _snake_case  :    Tuple						    =  [
         'CTRL_PRETRAINED_MODEL_ARCHIVE_LIST',
         'CTRLForSequenceClassification',
         'CTRLLMHeadModel',
         'CTRLModel',
         'CTRLPreTrainedModel',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _snake_case  :    Any						    =  [
         'TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST',
         'TFCTRLForSequenceClassification',
         'TFCTRLLMHeadModel',
         'TFCTRLModel',
         'TFCTRLPreTrainedModel',
     ]


if TYPE_CHECKING:
     from .configuration_ctrl import CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP, CTRLConfig
     from .tokenization_ctrl import CTRLTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_ctrl import (
              CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
              CTRLForSequenceClassification,
              CTRLLMHeadModel,
              CTRLModel,
              CTRLPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_ctrl import (
              TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFCTRLForSequenceClassification,
              TFCTRLLMHeadModel,
              TFCTRLModel,
              TFCTRLPreTrainedModel,
          )

else:
     import sys

     _snake_case  :    Any						    =  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








def 	UpperCamelCase__(       UpperCamelCase__			:       Dict  )->Dict:
       # if the collection is empty, returns empty
       if collection == []:
              return []

       # get some information about the collection
       A__											=						len(UpperCamelCase__  )
       A__											=						max(UpperCamelCase__  )
       A__											=						min(UpperCamelCase__  )

       # create the counting array
       A__											=						coll_max + 1 - coll_min
       A__											=						[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 ,     UpperCamelCase__  ):
              A__											=						counting_arr[i] + counting_arr[i - 1]

       # create the output collection
       A__											=						[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 ,     UpperCamelCase__  )  ):
              A__											=						collection[i]
              counting_arr[collection[i] - coll_min] -= 1

       return ordered


def 	UpperCamelCase__(       UpperCamelCase__			:       Optional[int]  )->Tuple:
       return "".join([chr(UpperCamelCase__  ) for i in counting_sort([ord(UpperCamelCase__  ) 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))





