import warnings
from collections import OrderedDict
from typing import Mapping

from packaging import version

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


_lowerCAmelCase       =		logging.get_logger(__name__)

_lowerCAmelCase       =		{
    "nvidia/segformer-b0-finetuned-ade-512-512": (
        "https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json"
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}
class     lowerCAmelCase_     (       __lowercase ):
							UpperCAmelCase				   =     "segformer"







							def __init__(   self      :     Optional[Any] ,			_A      :     List[Any]=3 ,			_A      :     Tuple=4 ,			_A      :     Any=[2, 2, 2, 2] ,			_A      :     Dict=[8, 4, 2, 1] ,			_A      :     int=[32, 64, 160, 256] ,			_A      :     Any=[7, 3, 3, 3] ,			_A      :     Any=[4, 2, 2, 2] ,			_A      :     str=[1, 2, 5, 8] ,			_A      :     Optional[Any]=[4, 4, 4, 4] ,			_A      :     Dict="gelu" ,			_A      :     Optional[Any]=0.0 ,			_A      :     Any=0.0 ,			_A      :     Tuple=0.1 ,			_A      :     Optional[Any]=0.02 ,			_A      :     Dict=0.1 ,			_A      :     Dict=1e-6 ,			_A      :     int=256 ,			_A      :     Dict=255 ,			**_A      :     List[Any] ,			):
												super().__init__(**_A		)

												if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
																	warnings.warn(
																	    '''Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be'''
																	    ''' removed, as the behaviour will default to that of reshape_last_stage = True.''' ,			_A ,			)

												_UpperCamelCase			     =     num_channels
												_UpperCamelCase			     =     num_encoder_blocks
												_UpperCamelCase			     =     depths
												_UpperCamelCase			     =     sr_ratios
												_UpperCamelCase			     =     hidden_sizes
												_UpperCamelCase			     =     patch_sizes
												_UpperCamelCase			     =     strides
												_UpperCamelCase			     =     mlp_ratios
												_UpperCamelCase			     =     num_attention_heads
												_UpperCamelCase			     =     hidden_act
												_UpperCamelCase			     =     hidden_dropout_prob
												_UpperCamelCase			     =     attention_probs_dropout_prob
												_UpperCamelCase			     =     classifier_dropout_prob
												_UpperCamelCase			     =     initializer_range
												_UpperCamelCase			     =     drop_path_rate
												_UpperCamelCase			     =     layer_norm_eps
												_UpperCamelCase			     =     decoder_hidden_size
												_UpperCamelCase			     =     kwargs.get('''reshape_last_stage''' ,			_A		)
												_UpperCamelCase			     =     semantic_loss_ignore_index




class     lowerCAmelCase_     (       __lowercase ):
							UpperCAmelCase				   =     version.parse("1.11" )







							@property
							def  UpperCamelCase_						(   self      :     Any		):
												return OrderedDict(
												    [
												        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
												    ]		)







							@property
							def  UpperCamelCase_						(   self      :     str		):
												return 1e-4







							@property
							def  UpperCamelCase_						(   self      :     int		):
												return 12







"""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""")
