





from typing import Callable, Optional, Union

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


__lowercase	: Optional[int]       =logging.get_logger(__name__)

__lowercase	: Optional[Any]       ={
    """microsoft/xprophetnet-large-wiki100-cased""": (
        """https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json"""
    ),
}

class   A							(						__lowercase    ):
      _snake_case				  ='''xlm-prophetnet'''
      _snake_case				  =['''past_key_values''']
      _snake_case				  ={
          '''num_attention_heads''': '''num_encoder_attention_heads''',
      }



      def __init__(						self:    int		,	_lowerCAmelCase:    Optional[float] = 0.1		,	_lowerCAmelCase:    Optional[Union[str, Callable]] = "gelu"		,	_lowerCAmelCase:    Optional[int] = 3_0522		,	_lowerCAmelCase:    Optional[int] = 1024		,	_lowerCAmelCase:    Optional[int] = 4096		,	_lowerCAmelCase:    Optional[int] = 12		,	_lowerCAmelCase:    Optional[int] = 16		,	_lowerCAmelCase:    Optional[int] = 4096		,	_lowerCAmelCase:    Optional[int] = 12		,	_lowerCAmelCase:    Optional[int] = 16		,	_lowerCAmelCase:    Optional[float] = 0.1		,	_lowerCAmelCase:    Optional[float] = 0.1		,	_lowerCAmelCase:    Optional[int] = 512		,	_lowerCAmelCase:    Optional[float] = 0.02		,	_lowerCAmelCase:    Optional[bool] = True		,	_lowerCAmelCase:    Optional[bool] = True		,	_lowerCAmelCase:    Optional[int] = 0		,	_lowerCAmelCase:    Optional[int] = 2		,	_lowerCAmelCase:    Optional[int] = 32		,	_lowerCAmelCase:    Optional[int] = 128		,	_lowerCAmelCase:    Optional[bool] = False		,	_lowerCAmelCase:    Optional[float] = 0.0		,	_lowerCAmelCase:    Optional[bool] = True		,	_lowerCAmelCase:    Optional[int] = 0		,	_lowerCAmelCase:    Optional[int] = 1		,	_lowerCAmelCase:    Optional[int] = 2		,	**_lowerCAmelCase:    str		,	)    ->     Optional[int]:
         '''simple docstring'''

         UpperCAmelCase_           =vocab_size
         UpperCAmelCase_           =hidden_size
         UpperCAmelCase_           =encoder_ffn_dim
         UpperCAmelCase_           =num_encoder_layers
         UpperCAmelCase_           =num_encoder_attention_heads
         UpperCAmelCase_           =decoder_ffn_dim
         UpperCAmelCase_           =num_decoder_layers
         UpperCAmelCase_           =num_decoder_attention_heads
         UpperCAmelCase_           =max_position_embeddings
         UpperCAmelCase_           =init_std  # Normal(0, this parameter)
         UpperCAmelCase_           =activation_function

         # parameters for xlmprophetnet
         UpperCAmelCase_           =ngram
         UpperCAmelCase_           =num_buckets
         UpperCAmelCase_           =relative_max_distance
         UpperCAmelCase_           =disable_ngram_loss
         UpperCAmelCase_           =eps

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

         UpperCAmelCase_           =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 						lowerCAmelCase__     (						self:    List[Any]							)    ->     int:
         '''simple docstring'''

         return self.num_encoder_layers + self.num_decoder_layers






      @num_hidden_layers.setter
      def 						lowerCAmelCase__     (						self:    Tuple		,	_lowerCAmelCase:    Optional[int]							)    ->     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`."							)











"""simple docstring"""





import csv

import tweepy

# Twitter API credentials
__A											=						""""""
__A											=						""""""
__A											=						""""""
__A											=						""""""
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->None:





  """simple docstring"""


  lowerCAmelCase__     :Any											=				tweepy.OAuthHandler(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )
  auth.set_access_token(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )
  lowerCAmelCase__     :List[Any]											=				tweepy.API(_SCREAMING_SNAKE_CASE     )

  # initialize a list to hold all the tweepy Tweets
  lowerCAmelCase__     :Union[str, Any]											=				[]

  # make initial request for most recent tweets (200 is the maximum allowed count)
  lowerCAmelCase__     :Optional[Any]											=				api.user_timeline(screen_name=_SCREAMING_SNAKE_CASE	,  count=200     )

  # save most recent tweets
  alltweets.extend(_SCREAMING_SNAKE_CASE     )

  # save the id of the oldest tweet less one
  lowerCAmelCase__     :Tuple											=				alltweets[-1].id - 1

  # keep grabbing tweets until there are no tweets left to grab
  while len(_SCREAMING_SNAKE_CASE     ) > 0:
    print(F"getting tweets before {oldest}"     )

    # all subsequent requests use the max_id param to prevent duplicates
    lowerCAmelCase__     :Union[str, Any]											=				api.user_timeline(
        screen_name=_SCREAMING_SNAKE_CASE	,  count=200	,  max_id=_SCREAMING_SNAKE_CASE     )

    # save most recent tweets
    alltweets.extend(_SCREAMING_SNAKE_CASE     )

    # update the id of the oldest tweet less one
    lowerCAmelCase__     :Tuple											=				alltweets[-1].id - 1

    print(F"...{len(_SCREAMING_SNAKE_CASE     )} tweets downloaded so far"     )

  # transform the tweepy tweets into a 2D array that will populate the csv
  lowerCAmelCase__     :Optional[Any]											=				[[tweet.id_str, tweet.created_at, tweet.text] for tweet in alltweets]

  # write the csv
  with open(F"new_{screen_name}_tweets.csv"	,  'w'     ) as f:
    lowerCAmelCase__     :List[str]											=				csv.writer(_SCREAMING_SNAKE_CASE     )
    writer.writerow(['id', 'created_at', 'text']     )
    writer.writerows(_SCREAMING_SNAKE_CASE     )


if __name__ == "__main__":
  # pass in the username of the account you want to download
  get_all_tweets("""FirePing32""")
