






class    __lowercase   :







     '''simple docstring'''




     def __init__(					self							:      Optional[int]			,						UpperCamelCase_							:      Optional[Any]					):


         """simple docstring"""



         __A       =						val
         __A       =						None
         __A       =						None





     def 		lowerCAmelCase_  (					self							:      Tuple			,						UpperCamelCase_							:      Union[str, Any]					):


         """simple docstring"""



         if self.val:
             if val < self.val:
                 if self.left is None:
                     __A       =						Node(UpperCamelCase_					)
                 else:
                     self.left.insert(UpperCamelCase_					)
             elif val > self.val:
                 if self.right is None:
                     __A       =						Node(UpperCamelCase_					)
                 else:
                     self.right.insert(UpperCamelCase_					)
         else:
             __A       =						val



def       _SCREAMING_SNAKE_CASE    (			__lowercase :      Dict      ,					__lowercase :      Tuple     )    ->   List[str]:





    """simple docstring"""

    if root:
        inorder(root.left      ,					__lowercase     )
        res.append(root.val     )
        inorder(root.right      ,					__lowercase     )



def       _SCREAMING_SNAKE_CASE    (			__lowercase :      Any     )    ->   Tuple:





    """simple docstring"""

    if len(__lowercase     ) == 0:
        return arr
    __A       =						Node(arr[0]     )
    for i in range(1      ,					len(__lowercase     )     ):
        root.insert(arr[i]     )
    # Traverse BST in order.
    __A       =						[]
    inorder(__lowercase      ,					__lowercase     )
    return res


if __name__ == "__main__":
  print(tree_sort([10, 1, 3, 2, 9, 14, 13]))












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


__a   :							Dict						= logging.get_logger(__name__)

__a   :							Dict						= {
    "bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}


class    __lowercase   (						lowercase_	):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE     =					"gpt_bigcode"
     SCREAMING_SNAKE_CASE     =					["past_key_values"]
     SCREAMING_SNAKE_CASE     =					{
         "hidden_size": "n_embd",
         "max_position_embeddings": "n_positions",
         "num_attention_heads": "n_head",
         "num_hidden_layers": "n_layer",
     }




     def __init__(					self							:      List[str]			,						UpperCamelCase_							:      Dict=50_257			,						UpperCamelCase_							:      int=1_024			,						UpperCamelCase_							:      List[Any]=768			,						UpperCamelCase_							:      str=12			,						UpperCamelCase_							:      Union[str, Any]=12			,						UpperCamelCase_							:      Optional[Any]=None			,						UpperCamelCase_							:      Tuple="gelu_pytorch_tanh"			,						UpperCamelCase_							:      Optional[Any]=0.1			,						UpperCamelCase_							:      List[str]=0.1			,						UpperCamelCase_							:      Optional[int]=0.1			,						UpperCamelCase_							:      int=1e-5			,						UpperCamelCase_							:      Tuple=0.02			,						UpperCamelCase_							:      Any=True			,						UpperCamelCase_							:      List[Any]=True			,						UpperCamelCase_							:      Dict=50_256			,						UpperCamelCase_							:      Optional[Any]=50_256			,						UpperCamelCase_							:      int=True			,						UpperCamelCase_							:      List[Any]=True			,						UpperCamelCase_							:      List[Any]=True			,						**UpperCamelCase_							:      int			,						):


         """simple docstring"""



         __A       =						vocab_size
         __A       =						n_positions
         __A       =						n_embd
         __A       =						n_layer
         __A       =						n_head
         __A       =						n_inner
         __A       =						activation_function
         __A       =						resid_pdrop
         __A       =						embd_pdrop
         __A       =						attn_pdrop
         __A       =						layer_norm_epsilon
         __A       =						initializer_range
         __A       =						scale_attn_weights
         __A       =						use_cache
         __A       =						attention_softmax_in_fpaa
         __A       =						scale_attention_softmax_in_fpaa
         __A       =						multi_query

         __A       =						bos_token_id
         __A       =						eos_token_id

         super().__init__(bos_token_id=UpperCamelCase_			,						eos_token_id=UpperCamelCase_			,						**UpperCamelCase_					)




