


from __future__ import annotations

SCREAMING_SNAKE_CASE	:Optional[int]  		=     [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]


class     __lowerCAmelCase     :






  """simple docstring"""





  def __init__(     self       :       str    ,				_lowerCAmelCase       :       int  )   -> None:




     """simple docstring"""
     snake_case_					    =					-1
     snake_case_					    =					-1
     snake_case_					    =					[-1] * length
     snake_case_					    =					None
     snake_case_					    =					None



  def __repr__(     self       :       Dict  )   -> str:




     """simple docstring"""
     return F'''Node(min_value={self.minn} max_value={self.maxx})'''






def 			_lowerCAmelCase						(							lowerCAmelCase_							:list[int]							)->Node | None:
   '''simple docstring'''






   snake_case_					    =					Node(len(lowerCAmelCase_							)							)
   snake_case_    ,    snake_case_					    =					min(lowerCAmelCase_							), max(lowerCAmelCase_							)
   # Leaf node case where the node contains only one unique value
   if root.minn == root.maxx:
      return root
   snake_case_					    =					(root.minn + root.maxx) // 2

   snake_case_					    =					[]
   snake_case_					    =					[]

   for index, num in enumerate(lowerCAmelCase_							):
      if num <= pivot:
         left_arr.append(lowerCAmelCase_							)
      else:
         right_arr.append(lowerCAmelCase_							)
      snake_case_					    =					len(lowerCAmelCase_							)
   snake_case_					    =					build_tree(lowerCAmelCase_							)
   snake_case_					    =					build_tree(lowerCAmelCase_							)
   return root



def 			_lowerCAmelCase						(							lowerCAmelCase_							:Node | None		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							:int							)->int:
   '''simple docstring'''






   if index < 0 or node is None:
      return 0
   # Leaf node cases
   if node.minn == node.maxx:
      return index + 1 if node.minn == num else 0
   snake_case_					    =					(node.minn + node.maxx) // 2
   if num <= pivot:
      # go the left subtree and map index to the left subtree
      return rank_till_index(node.left		,						lowerCAmelCase_		,						node.map_left[index] - 1							)
   else:
      # go to the right subtree and map index to the right subtree
      return rank_till_index(node.right		,						lowerCAmelCase_		,						index - node.map_left[index]							)



def 			_lowerCAmelCase						(							lowerCAmelCase_							:Node | None		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							:int							)->int:
   '''simple docstring'''






   if start > end:
      return 0
   snake_case_					    =					rank_till_index(lowerCAmelCase_		,						lowerCAmelCase_		,						lowerCAmelCase_							)
   snake_case_					    =					rank_till_index(lowerCAmelCase_		,						lowerCAmelCase_		,						start - 1							)
   return rank_till_end - rank_before_start



def 			_lowerCAmelCase						(							lowerCAmelCase_							:Node | None		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							:int							)->int:
   '''simple docstring'''






   if index > (end - start) or start > end or node is None:
      return -1
   # Leaf node case
   if node.minn == node.maxx:
      return node.minn
   # Number of elements in the left subtree in interval [start, end]
   snake_case_					    =					node.map_left[end] - (
       node.map_left[start - 1] if start else 0
   )
   if num_elements_in_left_tree > index:
      return quantile(
          node.left		,						lowerCAmelCase_		,						(node.map_left[start - 1] if start else 0)		,						node.map_left[end] - 1		,						)
   else:
      return quantile(
          node.right		,						index - num_elements_in_left_tree		,						start - (node.map_left[start - 1] if start else 0)		,						end - node.map_left[end]		,						)



def 			_lowerCAmelCase						(							lowerCAmelCase_							:Node | None		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							:int							)->int:
   '''simple docstring'''






   if (
       start > end
       or node is None
       or start_num > end_num
       or node.minn > end_num
       or node.maxx < start_num
   ):
      return 0
   if start_num <= node.minn and node.maxx <= end_num:
      return end - start + 1
   snake_case_					    =					range_counting(
       node.left		,						(node.map_left[start - 1] if start else 0)		,						node.map_left[end] - 1		,						lowerCAmelCase_		,						lowerCAmelCase_		,						)
   snake_case_					    =					range_counting(
       node.right		,						start - (node.map_left[start - 1] if start else 0)		,						end - node.map_left[end]		,						lowerCAmelCase_		,						lowerCAmelCase_		,						)
   return left + right


if __name__ == "__main__":
   import doctest

   doctest.testmod()








from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


SCREAMING_SNAKE_CASE	:int  		=     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE	:Optional[Any]  		=     {
    '''google/long-t5-local-base''': '''https://huggingface.co/google/long-t5-local-base/blob/main/config.json''',
    '''google/long-t5-local-large''': '''https://huggingface.co/google/long-t5-local-large/blob/main/config.json''',
    '''google/long-t5-tglobal-base''': '''https://huggingface.co/google/long-t5-tglobal-base/blob/main/config.json''',
    '''google/long-t5-tglobal-large''': '''https://huggingface.co/google/long-t5-tglobal-large/blob/main/config.json''',
}


class     __lowerCAmelCase     ( a					):






  """simple docstring"""





  _SCREAMING_SNAKE_CASE		    =       'longt5'
  _SCREAMING_SNAKE_CASE		    =       ['past_key_values']
  _SCREAMING_SNAKE_CASE		    =       {'hidden_size': 'd_model', 'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}



  def __init__(     self       :       int    ,				_lowerCAmelCase       :       str=3_2_1_2_8    ,				_lowerCAmelCase       :       Optional[Any]=5_1_2    ,				_lowerCAmelCase       :       List[str]=6_4    ,				_lowerCAmelCase       :       Optional[int]=2_0_4_8    ,				_lowerCAmelCase       :       Any=6    ,				_lowerCAmelCase       :       Any=None    ,				_lowerCAmelCase       :       str=8    ,				_lowerCAmelCase       :       List[str]=1_2_7    ,				_lowerCAmelCase       :       int=1_6    ,				_lowerCAmelCase       :       List[str]=3_2    ,				_lowerCAmelCase       :       Any=1_2_8    ,				_lowerCAmelCase       :       Union[str, Any]=0.1    ,				_lowerCAmelCase       :       Union[str, Any]=1e-6    ,				_lowerCAmelCase       :       str=1.0    ,				_lowerCAmelCase       :       Tuple="relu"    ,				_lowerCAmelCase       :       List[str]=True    ,				_lowerCAmelCase       :       Tuple="local"    ,				_lowerCAmelCase       :       Union[str, Any]=True    ,				_lowerCAmelCase       :       Optional[int]=0    ,				_lowerCAmelCase       :       str=1    ,				**_lowerCAmelCase       :       int    ,				)   -> Optional[int]:




     """simple docstring"""
     snake_case_					    =					vocab_size
     snake_case_					    =					d_model
     snake_case_					    =					d_kv
     snake_case_					    =					d_ff
     snake_case_					    =					num_layers
     # default = symmetry
     snake_case_					    =					num_decoder_layers if num_decoder_layers is not None else self.num_layers
     snake_case_					    =					num_heads
     snake_case_					    =					local_radius
     snake_case_					    =					global_block_size
     snake_case_					    =					relative_attention_num_buckets
     snake_case_					    =					relative_attention_max_distance
     snake_case_					    =					dropout_rate
     snake_case_					    =					layer_norm_epsilon
     snake_case_					    =					initializer_factor
     snake_case_					    =					feed_forward_proj
     snake_case_					    =					encoder_attention_type
     snake_case_					    =					use_cache

     snake_case_					    =					self.feed_forward_proj.split("-"  )
     snake_case_					    =					act_info[-1]
     snake_case_					    =					act_info[0] == "gated"

     if len(_lowerCAmelCase  ) > 1 and act_info[0] != "gated" or len(_lowerCAmelCase  ) > 2:
        raise ValueError(
            F'''`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer.'''
            "Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. "
            "'gated-gelu' or 'relu'"  )

     # for backwards compatibility
     if feed_forward_proj == "gated-gelu":
        snake_case_					    =					"gelu_new"

     super().__init__(
         pad_token_id=_lowerCAmelCase    ,				eos_token_id=_lowerCAmelCase    ,				is_encoder_decoder=_lowerCAmelCase    ,				**_lowerCAmelCase    ,				)






class     __lowerCAmelCase     ( a					):






  """simple docstring"""





  @property
  def 					lowerCAmelCase__  (     self       :       str  )   -> Mapping[str, Mapping[int, str]]:




     """simple docstring"""
     snake_case_					    =					{
         "input_ids": {0: "batch", 1: "encoder_sequence"},
         "attention_mask": {0: "batch", 1: "encoder_sequence"},
     }
     if self.use_past:
        snake_case_					    =					"past_encoder_sequence + sequence"
        snake_case_					    =					{0: "batch"}
        snake_case_					    =					{0: "batch", 1: "past_decoder_sequence + sequence"}
     else:
        snake_case_					    =					{0: "batch", 1: "decoder_sequence"}
        snake_case_					    =					{0: "batch", 1: "decoder_sequence"}

     if self.use_past:
        self.fill_with_past_key_values_(_lowerCAmelCase    ,				direction="inputs"  )

     return common_inputs



  @property
  def 					lowerCAmelCase__  (     self       :       List[Any]  )   -> int:




     """simple docstring"""
     return 1_3




