




from typing import Callable, Optional, Union

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


_lowerCamelCase							=      logging.get_logger(__name__)

_lowerCamelCase							=      {
    '''microsoft/prophetnet-large-uncased''': (
        '''https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json'''
    ),
}


class        UpperCAmelCase__				(							a__				):



     '''simple docstring'''
     _SCREAMING_SNAKE_CASE      :					Union[str, Any]     					=    'prophetnet'
     _SCREAMING_SNAKE_CASE      :					Tuple     					=    ['past_key_values']
     _SCREAMING_SNAKE_CASE      :					str     					=    {
         '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 = 0.02 ,    _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 ,    ):
            a			   =vocab_size
            a			   =hidden_size
            a			   =encoder_ffn_dim
            a			   =num_encoder_layers
            a			   =num_encoder_attention_heads
            a			   =decoder_ffn_dim
            a			   =num_decoder_layers
            a			   =num_decoder_attention_heads
            a			   =max_position_embeddings
            a			   =init_std  # Normal(0, this parameter)
            a			   =activation_function

            # parameters for prophetnet
            a			   =ngram
            a			   =num_buckets
            a			   =relative_max_distance
            a			   =disable_ngram_loss
            a			   =eps

            # 3 Types of Dropout
            a			   =attention_dropout
            a			   =activation_dropout
            a			   =dropout

            a			   =use_cache

            super().__init__(
                pad_token_id=__UpperCAmelCase ,    bos_token_id=__UpperCAmelCase ,    eos_token_id=__UpperCAmelCase ,    is_encoder_decoder=__UpperCAmelCase ,    add_cross_attention=__UpperCAmelCase ,    decoder_start_token_id=__UpperCAmelCase ,    **__UpperCAmelCase ,    )
     @property
     def        lowerCAmelCase__  (				self	):
            return self.num_encoder_layers + self.num_decoder_layers






     @num_hidden_layers.setter
     def        lowerCAmelCase__  (				self ,    _lowerCAmelCase	):
            raise NotImplementedError(
                """This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and"""
                """ `num_decoder_layers`."""	)




"""simple docstring"""






def    A_ ( _lowerCAmelCase  :       str							):






     """simple docstring"""

     return "".join(chr(ord(_lowerCAmelCase							) + 32							) if '''A''' <= char <= '''Z''' else char for char in word							)


if __name__ == "__main__":
   from doctest import testmod

   testmod()