


from typing import Callable, Optional, Union

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


__lowerCAmelCase			=							logging.get_logger(__name__)

__lowerCAmelCase			=							{
    '''microsoft/xprophetnet-large-wiki100-cased''': (
        '''https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json'''
    ),
}





class   __a      (   __UpperCamelCase				):
 __lowercase			:							Dict       					=			'xlm-prophetnet'
 __lowercase			:							Optional[int]       					=			['past_key_values']
 __lowercase			:							Tuple       					=			{
     'num_attention_heads': 'num_encoder_attention_heads',
 }
 def __init__(       self    ,			lowerCAmelCase__ = 0.1    ,			lowerCAmelCase__ = "gelu"    ,			lowerCAmelCase__ = 30_522    ,			lowerCAmelCase__ = 1_024    ,			lowerCAmelCase__ = 4_096    ,			lowerCAmelCase__ = 12    ,			lowerCAmelCase__ = 16    ,			lowerCAmelCase__ = 4_096    ,			lowerCAmelCase__ = 12    ,			lowerCAmelCase__ = 16    ,			lowerCAmelCase__ = 0.1    ,			lowerCAmelCase__ = 0.1    ,			lowerCAmelCase__ = 512    ,			lowerCAmelCase__ = 0.0_2    ,			lowerCAmelCase__ = True    ,			lowerCAmelCase__ = True    ,			lowerCAmelCase__ = 0    ,			lowerCAmelCase__ = 2    ,			lowerCAmelCase__ = 32    ,			lowerCAmelCase__ = 128    ,			lowerCAmelCase__ = False    ,			lowerCAmelCase__ = 0.0    ,			lowerCAmelCase__ = True    ,			lowerCAmelCase__ = 0    ,			lowerCAmelCase__ = 1    ,			lowerCAmelCase__ = 2    ,			**lowerCAmelCase__    ,			) ->    int:




        '''simple docstring'''
        lowercase__:       Optional[Any]        =       vocab_size
        lowercase__:       Dict        =       hidden_size
        lowercase__:       Optional[Any]        =       encoder_ffn_dim
        lowercase__:       List[Any]        =       num_encoder_layers
        lowercase__:       Optional[Any]        =       num_encoder_attention_heads
        lowercase__:       Union[str, Any]        =       decoder_ffn_dim
        lowercase__:       int        =       num_decoder_layers
        lowercase__:       Optional[Any]        =       num_decoder_attention_heads
        lowercase__:       List[Any]        =       max_position_embeddings
        lowercase__:       Tuple        =       init_std  # Normal(0, this parameter)
        lowercase__:       int        =       activation_function

        # parameters for xlmprophetnet
        lowercase__:       Optional[int]        =       ngram
        lowercase__:       Optional[Any]        =       num_buckets
        lowercase__:       Dict        =       relative_max_distance
        lowercase__:       Dict        =       disable_ngram_loss
        lowercase__:       Union[str, Any]        =       eps

        # 3 Types of Dropout
        lowercase__:       Any        =       attention_dropout
        lowercase__:       List[str]        =       activation_dropout
        lowercase__:       Union[str, Any]        =       dropout

        lowercase__:       int        =       use_cache

        super().__init__(
            pad_token_id=lowerCAmelCase__    ,			bos_token_id=lowerCAmelCase__    ,			eos_token_id=lowerCAmelCase__    ,			is_encoder_decoder=lowerCAmelCase__    ,			add_cross_attention=lowerCAmelCase__    ,			decoder_start_token_id=lowerCAmelCase__    ,			**lowerCAmelCase__    ,			)
 @property
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    int:




        '''simple docstring'''
        return self.num_encoder_layers + self.num_decoder_layers
 @num_hidden_layers.setter
 def 		SCREAMING_SNAKE_CASE__       (       self    ,			lowerCAmelCase__			) ->    Tuple:




        '''simple docstring'''
        raise NotImplementedError(
            'This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'
            ' `num_decoder_layers`.'			)






def        snake_case_					(  snake_case					)  ->    list[int]:
       lowercase__:       Dict        =       [0 for i in range(len(snake_case					)					)]

       # initialize interval's left pointer and right pointer
       lowercase__      ,						lowercase__:       Union[str, Any]        =       0, 0

       for i in range(1      ,							len(snake_case					)					):
              # case when current index is inside the interval
              if i <= right_pointer:
                     lowercase__:       List[Any]        =       min(right_pointer - i + 1      ,							z_result[i - left_pointer]					)
                     lowercase__:       List[str]        =       min_edge

              while go_next(snake_case      ,							snake_case      ,							snake_case					):
                     z_result[i] += 1

              # if new index's result gives us more right interval,
              # we've to update left_pointer and right_pointer
              if i + z_result[i] - 1 > right_pointer:
                     lowercase__      ,						lowercase__:       List[Any]        =       i, i + z_result[i] - 1

       return z_result




def        snake_case_					(  snake_case      ,							snake_case      ,							snake_case					)  ->    bool:
       return i + z_result[i] < len(snake_case					) and s[z_result[i]] == s[i + z_result[i]]




def        snake_case_					(  snake_case      ,							snake_case					)  ->    int:
       lowercase__:       Tuple        =       0
       # concatenate 'pattern' and 'input_str' and call z_function
       # with concatenated string
       lowercase__:       Any        =       z_function(pattern + input_str					)

       for val in z_result:
              # if value is greater then length of the pattern string
              # that means this index is starting position of substring
              # which is equal to pattern string
              if val >= len(snake_case					):
                     answer += 1

       return answer


if __name__ == "__main__":
 import doctest

 doctest.testmod()


