

'''simple docstring'''







import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__lowerCamelCase						    =      logging.get_logger(__name__)

__lowerCamelCase						    =      {"vocab_file": "sentencepiece.bpe.model"}

__lowerCamelCase						    =      {
    "vocab_file": {
        "moussaKam/mbarthez": "https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model",
        "moussaKam/barthez": "https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model",
        "moussaKam/barthez-orangesum-title": (
            "https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model"
        ),
    },
}

__lowerCamelCase						    =      {
    "moussaKam/mbarthez": 1024,
    "moussaKam/barthez": 1024,
    "moussaKam/barthez-orangesum-title": 1024,
}

__lowerCamelCase						    =      "▁"






class    A__ ( SCREAMING_SNAKE_CASE__     ):
    lowercase		   =						VOCAB_FILES_NAMES
    lowercase		   =						PRETRAINED_VOCAB_FILES_MAP
    lowercase		   =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowercase		   =						['''input_ids''', '''attention_mask''']



    def __init__(   self						,			UpperCamelCase__						,			UpperCamelCase__="<s>"						,			UpperCamelCase__="</s>"						,			UpperCamelCase__="</s>"						,			UpperCamelCase__="<s>"						,			UpperCamelCase__="<unk>"						,			UpperCamelCase__="<pad>"						,			UpperCamelCase__="<mask>"						,			UpperCamelCase__ = None						,			**UpperCamelCase__						,			)  -> str:





           '''simple docstring'''
           # Mask token behave like a normal word, i.e. include the space before it
           A_		   = AddedToken(A__						,			lstrip=A__						,			rstrip=A__    ) if isinstance(A__						,			A__    ) else mask_token

           A_		   = {} if sp_model_kwargs is None else sp_model_kwargs

           super().__init__(
               bos_token=A__						,			eos_token=A__						,			unk_token=A__						,			sep_token=A__						,			cls_token=A__						,			pad_token=A__						,			mask_token=A__						,			sp_model_kwargs=self.sp_model_kwargs						,			**A__						,			)

           A_		   = vocab_file
           A_		   = spm.SentencePieceProcessor(**self.sp_model_kwargs    )
           self.sp_model.Load(str(A__    )    )

           A_		   = {"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

           A_		   = len(self.sp_model    ) - 1
           A_		   = {v: k for k, v in self.fairseq_tokens_to_ids.items()}



    def    snake_case_     (   self						,			UpperCamelCase__						,			UpperCamelCase__ = None    )  -> Tuple:





           '''simple docstring'''

           if token_ids_a is None:
                  return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
           A_		   = [self.cls_token_id]
           A_		   = [self.sep_token_id]
           return cls + token_ids_a + sep + sep + token_ids_a + sep



    def    snake_case_     (   self						,			UpperCamelCase__						,			UpperCamelCase__ = None						,			UpperCamelCase__ = False    )  -> Optional[int]:





           '''simple docstring'''
           if already_has_special_tokens:
                  return super().get_special_tokens_mask(
                      token_ids_a=A__						,			token_ids_a=A__						,			already_has_special_tokens=A__    )

           if token_ids_a is None:
                  return [1] + ([0] * len(A__    )) + [1]
           return [1] + ([0] * len(A__    )) + [1, 1] + ([0] * len(A__    )) + [1]



    def    snake_case_     (   self						,			UpperCamelCase__						,			UpperCamelCase__ = None    )  -> str:





           '''simple docstring'''
           A_		   = [self.sep_token_id]
           A_		   = [self.cls_token_id]

           if token_ids_a is None:
                  return len(cls + token_ids_a + sep    ) * [0]
           return len(cls + token_ids_a + sep + sep + token_ids_a + sep    ) * [0]



    @property
    def    snake_case_     (   self    )  -> Tuple:





           '''simple docstring'''
           return len(self.sp_model    )



    def    snake_case_     (   self    )  -> Optional[Any]:





           '''simple docstring'''
           A_		   = {self.convert_ids_to_tokens(A__    ): i for i in range(self.vocab_size    )}
           vocab.update(self.added_tokens_encoder    )
           return vocab



    def    snake_case_     (   self						,			UpperCamelCase__    )  -> int:





           '''simple docstring'''
           return self.sp_model.encode(A__						,			out_type=A__    )



    def    snake_case_     (   self						,			UpperCamelCase__    )  -> str:





           '''simple docstring'''
           if token in self.fairseq_tokens_to_ids:
                  return self.fairseq_tokens_to_ids[token]
           A_		   = self.sp_model.PieceToId(A__    )

           return spm_id if spm_id else self.unk_token_id



    def    snake_case_     (   self						,			UpperCamelCase__    )  -> List[str]:





           '''simple docstring'''
           if index in self.fairseq_ids_to_tokens:
                  return self.fairseq_ids_to_tokens[index]
           return self.sp_model.IdToPiece(A__    )



    def    snake_case_     (   self						,			UpperCamelCase__    )  -> Tuple:





           '''simple docstring'''
           A_		   = []
           A_		   = """"""
           A_		   = False
           for token in tokens:
                  # make sure that special tokens are not decoded using sentencepiece model
                  if token in self.all_special_tokens:
                         if not prev_is_special:
                                out_string += " "
                         out_string += self.sp_model.decode(A__    ) + token
                         A_		   = True
                         A_		   = []
                  else:
                         current_sub_tokens.append(A__    )
                         A_		   = False
           out_string += self.sp_model.decode(A__    )
           return out_string.strip()



    def __getstate__(   self    )  -> Dict:





           '''simple docstring'''
           A_		   = self.__dict__.copy()
           A_		   = None
           return state



    def __setstate__(   self						,			UpperCamelCase__    )  -> List[str]:





           '''simple docstring'''
           A_		   = d

           # for backward compatibility
           if not hasattr(self						,			"""sp_model_kwargs"""    ):
                  A_		   = {}

           A_		   = spm.SentencePieceProcessor(**self.sp_model_kwargs    )
           self.sp_model.Load(self.vocab_file    )







    def    snake_case_     (   self						,			UpperCamelCase__						,			UpperCamelCase__ = None    )  -> int:





           '''simple docstring'''
           if not os.path.isdir(A__    ):
                  logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''    )
                  return
           A_		   = os.path.join(
               A__						,			(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]    )

           if os.path.abspath(self.vocab_file    ) != os.path.abspath(A__    ) and os.path.isfile(self.vocab_file    ):
                  copyfile(self.vocab_file						,			A__    )
           elif not os.path.isfile(self.vocab_file    ):
                  with open(A__						,			"""wb"""    ) as fi:
                         A_		   = self.sp_model.serialized_model_proto()
                         fi.write(A__    )

           return (out_vocab_file,)



'''simple docstring'''







import requests

__lowerCamelCase						    =      ''''''  # <-- Put your OpenWeatherMap appid here!
__lowerCamelCase						    =      '''https://api.openweathermap.org/data/2.5/'''
def  UpperCAmelCase__      ( UpperCAmelCase__ = "Chicago",    UpperCAmelCase__ = APPID			)     ->     dict:
       return requests.get(URL_BASE + """weather""",    params=locals()			).json()
def  UpperCAmelCase__      ( UpperCAmelCase__ = "Kolkata, India",    UpperCAmelCase__ = APPID			)     ->     dict:
       return requests.get(URL_BASE + """forecast""",    params=locals()			).json()
def  UpperCAmelCase__      ( UpperCAmelCase__ = 55.68,    UpperCAmelCase__ = 12.57,    UpperCAmelCase__ = APPID			)     ->     dict:
       return requests.get(URL_BASE + """onecall""",    params=locals()			).json()


if __name__ == "__main__":
      from pprint import pprint

      while True:
            __lowerCamelCase						    =      input('''Enter a location:''').strip()
            if location:
                  pprint(current_weather(location))
            else:
                  break
