


"""simple docstring"""







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 				SCREAMING_SNAKE_CASE__    (		lowercase    ):
       """simple docstring"""


       a  :    Tuple       ="xlm-prophetnet"
       a  :    List[str]       =["past_key_values"]
       a  :    Optional[Any]       ={
           "num_attention_heads": "num_encoder_attention_heads",
       }

       def __init__(						self		,					snake_case__ = 0.1		,					snake_case__ = "gelu"		,					snake_case__ = 30_522		,					snake_case__ = 1_024		,					snake_case__ = 4_096		,					snake_case__ = 12		,					snake_case__ = 16		,					snake_case__ = 4_096		,					snake_case__ = 12		,					snake_case__ = 16		,					snake_case__ = 0.1		,					snake_case__ = 0.1		,					snake_case__ = 512		,					snake_case__ = 0.02		,					snake_case__ = True		,					snake_case__ = True		,					snake_case__ = 0		,					snake_case__ = 2		,					snake_case__ = 32		,					snake_case__ = 128		,					snake_case__ = False		,					snake_case__ = 0.0		,					snake_case__ = True		,					snake_case__ = 0		,					snake_case__ = 1		,					snake_case__ = 2		,					**snake_case__		,					):






         """simple docstring"""





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

         # parameters for xlmprophetnet
         lowerCAmelCase					:					List[Any]								=							ngram
         lowerCAmelCase					:					Tuple								=							num_buckets
         lowerCAmelCase					:					List[Any]								=							relative_max_distance
         lowerCAmelCase					:					str								=							disable_ngram_loss
         lowerCAmelCase					:					Optional[Any]								=							eps

         # 3 Types of Dropout
         lowerCAmelCase					:					List[Any]								=							attention_dropout
         lowerCAmelCase					:					Optional[int]								=							activation_dropout
         lowerCAmelCase					:					str								=							dropout

         lowerCAmelCase					:					Optional[int]								=							use_cache

         super().__init__(
             pad_token_id=snake_case__		,					bos_token_id=snake_case__		,					eos_token_id=snake_case__		,					is_encoder_decoder=snake_case__		,					add_cross_attention=snake_case__		,					decoder_start_token_id=snake_case__		,					**snake_case__		,					)

       @property
       def 	lowercase__							(						self						):






         """simple docstring"""





         return self.num_encoder_layers + self.num_decoder_layers







       @num_hidden_layers.setter
       def 	lowercase__							(						self		,					snake_case__						):






         """simple docstring"""





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









"""simple docstring"""







import re

from filelock import FileLock


try:
     import nltk

     lowerCAmelCase__				    =       True
except (ImportError, ModuleNotFoundError):
     lowerCAmelCase__				    =       False

if NLTK_AVAILABLE:
     with FileLock('''.lock''') as lock:
          nltk.download('''punkt''', quiet=True)
def  a__      (    SCREAMING_SNAKE_CASE   :   str    ):


  '''simple docstring'''







  re.sub("<n>"    ,				""    ,				SCREAMING_SNAKE_CASE    )  # remove pegasus newline char
  assert NLTK_AVAILABLE, "nltk must be installed to separate newlines between sentences. (pip install nltk)"
  return "\n".join(nltk.sent_tokenize(SCREAMING_SNAKE_CASE    )    )





