"""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


UpperCAmelCase__     						=  logging.get_logger(__name__)

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

UpperCAmelCase__     						=  {
    """vocab_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model""",
    }
}

UpperCAmelCase__     						=  {
    """camembert-base""": 5_1_2,
}

UpperCAmelCase__     						=  """▁"""


class 				a (						lowerCAmelCase_      ):
    _snake_case   :     Any   							=							VOCAB_FILES_NAMES
    _snake_case   :     List[Any]   							=							PRETRAINED_VOCAB_FILES_MAP
    _snake_case   :     str   							=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    _snake_case   :     Optional[int]   							=							['input_ids', 'attention_mask']


    def __init__(    self		:     List[str]      , __lowerCAmelCase		:     Union[str, Any]      , __lowerCAmelCase		:     Union[str, Any]="<s>"      , __lowerCAmelCase		:     Tuple="</s>"      , __lowerCAmelCase		:     List[Any]="</s>"      , __lowerCAmelCase		:     List[str]="<s>"      , __lowerCAmelCase		:     Optional[Any]="<unk>"      , __lowerCAmelCase		:     Dict="<pad>"      , __lowerCAmelCase		:     Optional[Any]="<mask>"      , __lowerCAmelCase		:     Optional[Any]=["<s>NOTUSED", "</s>NOTUSED"]      , __lowerCAmelCase		:     Optional[Dict[str, Any]] = None      , **__lowerCAmelCase		:     str      , ):
      # Mask token behave like a normal word, i.e. include the space before it
      _UpperCAmelCase         =					AddedToken(__lowerCAmelCase      , lstrip=__lowerCAmelCase      , rstrip=__lowerCAmelCase    ) if isinstance(__lowerCAmelCase      , __lowerCAmelCase    ) else mask_token

      _UpperCAmelCase         =					{} if sp_model_kwargs is None else sp_model_kwargs

      super().__init__(
          bos_token=__lowerCAmelCase      , eos_token=__lowerCAmelCase      , unk_token=__lowerCAmelCase      , sep_token=__lowerCAmelCase      , cls_token=__lowerCAmelCase      , pad_token=__lowerCAmelCase      , mask_token=__lowerCAmelCase      , additional_special_tokens=__lowerCAmelCase      , sp_model_kwargs=self.sp_model_kwargs      , **__lowerCAmelCase      , )
      _UpperCAmelCase         =					spm.SentencePieceProcessor(**self.sp_model_kwargs    )
      self.sp_model.Load(str(__lowerCAmelCase    )    )
      _UpperCAmelCase         =					vocab_file
      # HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
      # sentencepiece vocabulary (this is the case for <s> and </s>
      _UpperCAmelCase         =					{"""<s>NOTUSED""": 0, """<pad>""": 1, """</s>NOTUSED""": 2, """<unk>""": 3}
      _UpperCAmelCase         =					len(self.fairseq_tokens_to_ids    )
      _UpperCAmelCase         =					len(self.sp_model    ) + len(self.fairseq_tokens_to_ids    )
      _UpperCAmelCase         =					{v: k for k, v in self.fairseq_tokens_to_ids.items()}


    def    lowerCAmelCase_     (    self		:     Dict      , __lowerCAmelCase		:     List[int]      , __lowerCAmelCase		:     Optional[List[int]] = None    ):

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


    def    lowerCAmelCase_     (    self		:     Tuple      , __lowerCAmelCase		:     List[int]      , __lowerCAmelCase		:     Optional[List[int]] = None      , __lowerCAmelCase		:     bool = False    ):
      if already_has_special_tokens:
        return super().get_special_tokens_mask(
            token_ids_a=__lowerCAmelCase      , token_ids_a=__lowerCAmelCase      , already_has_special_tokens=__lowerCAmelCase    )

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


    def    lowerCAmelCase_     (    self		:     Optional[int]      , __lowerCAmelCase		:     List[int]      , __lowerCAmelCase		:     Optional[List[int]] = None    ):
      _UpperCAmelCase         =					[self.sep_token_id]
      _UpperCAmelCase         =					[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    lowerCAmelCase_     (    self		:     Tuple    ):
      return len(self.fairseq_tokens_to_ids    ) + len(self.sp_model    )


    def    lowerCAmelCase_     (    self		:     Tuple    ):
      _UpperCAmelCase         =					{self.convert_ids_to_tokens(__lowerCAmelCase    ): i for i in range(self.vocab_size    )}
      vocab.update(self.added_tokens_encoder    )
      return vocab


    def    lowerCAmelCase_     (    self		:     int      , __lowerCAmelCase		:     str    ):
      return self.sp_model.encode(__lowerCAmelCase      , out_type=__lowerCAmelCase    )


    def    lowerCAmelCase_     (    self		:     Tuple      , __lowerCAmelCase		:     Dict    ):
      if token in self.fairseq_tokens_to_ids:
        return self.fairseq_tokens_to_ids[token]
      elif self.sp_model.PieceToId(__lowerCAmelCase    ) == 0:
        # Convert sentence piece unk token to fairseq unk token index
        return self.unk_token_id
      return self.fairseq_offset + self.sp_model.PieceToId(__lowerCAmelCase    )


    def    lowerCAmelCase_     (    self		:     Tuple      , __lowerCAmelCase		:     str    ):
      if index in self.fairseq_ids_to_tokens:
        return self.fairseq_ids_to_tokens[index]
      return self.sp_model.IdToPiece(index - self.fairseq_offset    )


    def    lowerCAmelCase_     (    self		:     Optional[Any]      , __lowerCAmelCase		:     Optional[int]    ):
      _UpperCAmelCase         =					[]
      _UpperCAmelCase         =					""""""
      _UpperCAmelCase         =					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(__lowerCAmelCase    ) + token
          _UpperCAmelCase         =					True
          _UpperCAmelCase         =					[]
        else:
          current_sub_tokens.append(__lowerCAmelCase    )
          _UpperCAmelCase         =					False
      out_string += self.sp_model.decode(__lowerCAmelCase    )
      return out_string.strip()


    def __getstate__(    self		:     Tuple    ):
      _UpperCAmelCase         =					self.__dict__.copy()
      _UpperCAmelCase         =					None
      return state


    def __setstate__(    self		:     List[str]      , __lowerCAmelCase		:     int    ):
      _UpperCAmelCase         =					d

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

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


    def    lowerCAmelCase_     (    self		:     Dict      , __lowerCAmelCase		:     str      , __lowerCAmelCase		:     Optional[str] = None    ):
      if not os.path.isdir(__lowerCAmelCase    ):
        logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''    )
        return
      _UpperCAmelCase         =					os.path.join(
          __lowerCAmelCase      , (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]    )

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

      return (out_vocab_file,)

"""simple docstring"""


import requests

UpperCAmelCase__     						=  """"""  # <-- Put your OpenWeatherMap appid here!
UpperCAmelCase__     						=  """https://api.openweathermap.org/data/2.5/"""






def 			__UpperCAmelCase    (	lowercase = "Chicago"      ,lowercase = APPID						):







  """simple docstring"""
  return requests.get(URL_BASE + """weather"""      ,params=locals()						).json()






def 			__UpperCAmelCase    (	lowercase = "Kolkata, India"      ,lowercase = APPID						):







  """simple docstring"""
  return requests.get(URL_BASE + """forecast"""      ,params=locals()						).json()






def 			__UpperCAmelCase    (	lowercase = 55.68      ,lowercase = 12.57      ,lowercase = APPID						):







  """simple docstring"""
  return requests.get(URL_BASE + """onecall"""      ,params=locals()						).json()


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

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