






from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCamelCase	:		str										=   logging.get_logger(__name__)

__lowerCamelCase	:		Dict										=   {}







class  _lowercase   (   lowerCAmelCase__						):
      _a							:						int										=							"llama"
      _a							:						Union[str, Any]										=							["past_key_values"]
      def __init__(     self				,			a=3_2_0_0_0				,			a=4_0_9_6				,			a=1_1_0_0_8				,			a=3_2				,			a=3_2				,			a=None				,			a="silu"				,			a=2_0_4_8				,			a=0.02				,			a=1e-6				,			a=True				,			a=0				,			a=1				,			a=2				,			a=1				,			a=False				,			a=None				,			**a				,			):
       snake_case__  :    Any							       =vocab_size
       snake_case__  :    Dict							       =max_position_embeddings
       snake_case__  :    Optional[int]							       =hidden_size
       snake_case__  :    Dict							       =intermediate_size
       snake_case__  :    Tuple							       =num_hidden_layers
       snake_case__  :    Tuple							       =num_attention_heads

       # for backward compatibility
       if num_key_value_heads is None:
        snake_case__  :    int							       =num_attention_heads

       snake_case__  :    List[Any]							       =num_key_value_heads
       snake_case__  :    str							       =hidden_act
       snake_case__  :    Tuple							       =initializer_range
       snake_case__  :    str							       =rms_norm_eps
       snake_case__  :    Optional[Any]							       =pretraining_tp
       snake_case__  :    Union[str, Any]							       =use_cache
       snake_case__  :    Optional[Any]							       =rope_scaling
       self._rope_scaling_validation()

       super().__init__(
           pad_token_id=_SCREAMING_SNAKE_CASE				,			bos_token_id=_SCREAMING_SNAKE_CASE				,			eos_token_id=_SCREAMING_SNAKE_CASE				,			tie_word_embeddings=_SCREAMING_SNAKE_CASE				,			**_SCREAMING_SNAKE_CASE				,			)



      def 						lowercase__					(     self   ):
       if self.rope_scaling is None:
        return

       if not isinstance(self.rope_scaling				,			_SCREAMING_SNAKE_CASE   ) or len(self.rope_scaling   ) != 2:
        raise ValueError(
            """`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, """
            F"got {self.rope_scaling}"   )
       snake_case__  :    str							       =self.rope_scaling.get("""type"""				,			_SCREAMING_SNAKE_CASE   )
       snake_case__  :    str							       =self.rope_scaling.get("""factor"""				,			_SCREAMING_SNAKE_CASE   )
       if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
        raise ValueError(
            F"`rope_scaling`\'s name field must be one of [\'linear\', \'dynamic\'], got {rope_scaling_type}"   )
       if rope_scaling_factor is None or not isinstance(_SCREAMING_SNAKE_CASE				,			_SCREAMING_SNAKE_CASE   ) or rope_scaling_factor <= 1.0:
        raise ValueError(F"`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}"   )













import math







def 			A__							(      _a  :					list		,  _a  :					int = 0		,  _a  :					int = 0	):





 '''simple docstring'''







 snake_case__  :    Tuple							       =end or len(_a	)
 for i in range(_a		,  _a	):
  snake_case__  :    int							       =i
  snake_case__  :    int							       =array[i]
  while temp_index != start and temp_index_value < array[temp_index - 1]:
   snake_case__  :    Dict							       =array[temp_index - 1]
   temp_index -= 1
  snake_case__  :    Dict							       =temp_index_value
 return array







def 			A__							(      _a  :					list		,  _a  :					int		,  _a  :					int	):  # Max Heap





 '''simple docstring'''







 snake_case__  :    Tuple							       =index
 snake_case__  :    Dict							       =2 * index + 1  # Left Node
 snake_case__  :    Union[str, Any]							       =2 * index + 2  # Right Node

 if left_index < heap_size and array[largest] < array[left_index]:
  snake_case__  :    Dict							       =left_index

 if right_index < heap_size and array[largest] < array[right_index]:
  snake_case__  :    List[Any]							       =right_index

 if largest != index:
  snake_case__       ,   snake_case__  :    List[Any]							       =array[largest], array[index]
  heapify(_a		,  _a		,  _a	)







def 			A__							(      _a  :					list	):





 '''simple docstring'''







 snake_case__  :    List[str]							       =len(_a	)

 for i in range(n // 2		,  -1		,  -1	):
  heapify(_a		,  _a		,  _a	)

 for i in range(n - 1		,  0		,  -1	):
  snake_case__       ,   snake_case__  :    Tuple							       =array[0], array[i]
  heapify(_a		,  0		,  _a	)

 return array







def 			A__							(      _a  :					list		,  _a  :					int		,  _a  :					int		,  _a  :					int	):





 '''simple docstring'''







 if (array[first_index] > array[middle_index]) != (
     array[first_index] > array[last_index]
 ):
  return array[first_index]
 elif (array[middle_index] > array[first_index]) != (
     array[middle_index] > array[last_index]
 ):
  return array[middle_index]
 else:
  return array[last_index]







def 			A__							(      _a  :					list		,  _a  :					int		,  _a  :					int		,  _a  :					int	):





 '''simple docstring'''







 snake_case__  :    Dict							       =low
 snake_case__  :    Union[str, Any]							       =high
 while True:
  while array[i] < pivot:
   i += 1
  j -= 1
  while pivot < array[j]:
   j -= 1
  if i >= j:
   return i
  snake_case__       ,   snake_case__  :    List[Any]							       =array[j], array[i]
  i += 1







def 			A__							(      _a  :					list	):





 '''simple docstring'''







 if len(_a	) == 0:
  return array
 snake_case__  :    Optional[int]							       =2 * math.ceil(math.loga(len(_a	)	)	)
 snake_case__  :    Tuple							       =16
 return intro_sort(_a		,  0		,  len(_a	)		,  _a		,  _a	)







def 			A__							(      _a  :					list		,  _a  :					int		,  _a  :					int		,  _a  :					int		,  _a  :					int	):





 '''simple docstring'''







 while end - start > size_threshold:
  if max_depth == 0:
   return heap_sort(_a	)
  max_depth -= 1
  snake_case__  :    Dict							       =median_of_a(_a		,  _a		,  start + ((end - start) // 2) + 1		,  end - 1	)
  snake_case__  :    List[str]							       =partition(_a		,  _a		,  _a		,  _a	)
  intro_sort(_a		,  _a		,  _a		,  _a		,  _a	)
  snake_case__  :    Union[str, Any]							       =p
 return insertion_sort(_a		,  _a		,  _a	)


if __name__ == "__main__":
       import doctest

       doctest.testmod()

       __lowerCamelCase	:		Optional[int]										=   input("""Enter numbers separated by a comma : """).strip()
       __lowerCamelCase	:		Dict										=   [float(item) for item in user_input.split(""",""")]
       print(sort(unsorted))





