
"""simple docstring"""




from typing import Mapping

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


a		:					str    	=					logging.get_logger(__name__)

a		:					Dict    	=					{
    '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 						lowercase(_lowercase					):
     __snake_case:  Any  				=    'longt5'
     __snake_case:  Optional[Any]  				=    ['past_key_values']
     __snake_case:  List[Any]  				=    {'hidden_size': 'd_model', 'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}



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







         """simple docstring"""



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

         a__    = self.feed_forward_proj.split('-'      )
         a__    = act_info[-1]
         a__    = act_info[0] == 'gated'

         if len(__SCREAMING_SNAKE_CASE      ) > 1 and act_info[0] != "gated" or len(__SCREAMING_SNAKE_CASE      ) > 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":
             a__    = 'gelu_new'

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







class 						lowercase(_lowercase					):



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







         """simple docstring"""



         a__    = {
             'input_ids': {0: 'batch', 1: 'encoder_sequence'},
             'attention_mask': {0: 'batch', 1: 'encoder_sequence'},
         }
         if self.use_past:
             a__    = 'past_encoder_sequence + sequence'
             a__    = {0: 'batch'}
             a__    = {0: 'batch', 1: 'past_decoder_sequence + sequence'}
         else:
             a__    = {0: 'batch', 1: 'decoder_sequence'}
             a__    = {0: 'batch', 1: 'decoder_sequence'}

         if self.use_past:
             self.fill_with_past_key_values_(__SCREAMING_SNAKE_CASE    ,							direction='inputs'      )

         return common_inputs




     @property
     def  lowercase__     (       self      )		->    int:







         """simple docstring"""



         return 1_3




"""simple docstring"""




import math







class 						lowercase:



     def __init__(       self    ,							__SCREAMING_SNAKE_CASE      )		->    Optional[int]:







         """simple docstring"""



         a__    = len(__SCREAMING_SNAKE_CASE      )
         a__    = [0] * (
             4 * self.N
         )  # approximate the overall size of segment tree with array N
         self.build(1    ,							0    ,							self.N - 1      )



     def  lowercase__     (       self    ,							__SCREAMING_SNAKE_CASE      )		->    Optional[Any]:







         """simple docstring"""



         return idx * 2



     def  lowercase__     (       self    ,							__SCREAMING_SNAKE_CASE      )		->    Optional[int]:







         """simple docstring"""



         return idx * 2 + 1



     def  lowercase__     (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )		->    List[str]:  # noqa: E741







         """simple docstring"""



         if l == r:
             a__    = A[l]
         else:
             a__    = (l + r) // 2
             self.build(self.left(__SCREAMING_SNAKE_CASE      )    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )
             self.build(self.right(__SCREAMING_SNAKE_CASE      )    ,							mid + 1    ,							__SCREAMING_SNAKE_CASE      )
             a__    = max(self.st[self.left(__SCREAMING_SNAKE_CASE      )]    ,							self.st[self.right(__SCREAMING_SNAKE_CASE      )]      )



     def  lowercase__     (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )		->    int:







         """simple docstring"""



         return self.update_recursive(1    ,							0    ,							self.N - 1    ,							a - 1    ,							b - 1    ,							__SCREAMING_SNAKE_CASE      )



     def  lowercase__     (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )		->    Optional[int]:  # noqa: E741







         """simple docstring"""



         if r < a or l > b:
             return True
         if l == r:
             a__    = val
             return True
         a__    = (l + r) // 2
         self.update_recursive(self.left(__SCREAMING_SNAKE_CASE      )    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )
         self.update_recursive(self.right(__SCREAMING_SNAKE_CASE      )    ,							mid + 1    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )
         a__    = max(self.st[self.left(__SCREAMING_SNAKE_CASE      )]    ,							self.st[self.right(__SCREAMING_SNAKE_CASE      )]      )
         return True



     def  lowercase__     (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )		->    List[str]:







         """simple docstring"""



         return self.query_recursive(1    ,							0    ,							self.N - 1    ,							a - 1    ,							b - 1      )



     def  lowercase__     (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )		->    Any:  # noqa: E741







         """simple docstring"""



         if r < a or l > b:
             return -math.inf
         if l >= a and r <= b:
             return self.st[idx]
         a__    = (l + r) // 2
         a__    = self.query_recursive(self.left(__SCREAMING_SNAKE_CASE      )    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )
         a__    = self.query_recursive(self.right(__SCREAMING_SNAKE_CASE      )    ,							mid + 1    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )
         return max(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )




     def  lowercase__     (       self      )		->    List[Any]:







         """simple docstring"""



         a__    = []
         for i in range(1    ,							N + 1      ):
             show_list += [self.query(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )]
         print(__SCREAMING_SNAKE_CASE      )


if __name__ == "__main__":
    a		:					Union[str, Any]    	=					[1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
    a		:					Dict    	=					15
    a		:					Tuple    	=					SegmentTree(A)
    print(segt.query(4, 6))
    print(segt.query(7, 11))
    print(segt.query(7, 12))
    segt.update(1, 3, 1_11)
    print(segt.query(1, 15))
    segt.update(7, 8, 2_35)
    segt.show_data()


