"""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__			=    """▁"""

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

UpperCAmelCase__			=    {
    """vocab_file""": {
        """xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model""",
        """xlm-roberta-large""": """https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model""",
        """xlm-roberta-large-finetuned-conll02-dutch""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll02-spanish""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll03-english""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll03-german""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"""
        ),
    }
}

UpperCAmelCase__			=    {
    """xlm-roberta-base""": 5_1_2,
    """xlm-roberta-large""": 5_1_2,
    """xlm-roberta-large-finetuned-conll02-dutch""": 5_1_2,
    """xlm-roberta-large-finetuned-conll02-spanish""": 5_1_2,
    """xlm-roberta-large-finetuned-conll03-english""": 5_1_2,
    """xlm-roberta-large-finetuned-conll03-german""": 5_1_2,
}


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


    def __init__(       self						:	List[Any] ,					__lowerCAmelCase						:	Optional[Any] ,					__lowerCAmelCase						:	List[str]="<s>" ,					__lowerCAmelCase						:	List[str]="</s>" ,					__lowerCAmelCase						:	int="</s>" ,					__lowerCAmelCase						:	int="<s>" ,					__lowerCAmelCase						:	Optional[int]="<unk>" ,					__lowerCAmelCase						:	Dict="<pad>" ,					__lowerCAmelCase						:	str="<mask>" ,					__lowerCAmelCase						:	Optional[Dict[str, Any]] = None ,					**__lowerCAmelCase						:	Optional[int] ,					):
      # 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 ,					sp_model_kwargs=self.sp_model_kwargs ,					**__lowerCAmelCase ,					)

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

      # Original fairseq vocab and spm vocab must be "aligned":
      # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
      # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
      # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
      # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

      # Mimic fairseq token-to-id alignment for the first 4 token
      _UpperCAmelCase    			=   {"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

      # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
      _UpperCAmelCase    			=   1

      _UpperCAmelCase    			=   len(self.sp_model       ) + self.fairseq_offset
      _UpperCAmelCase    			=   {v: k for k, v in self.fairseq_tokens_to_ids.items()}


    def __getstate__(       self						:	Any       ):
      _UpperCAmelCase    			=   self.__dict__.copy()
      _UpperCAmelCase    			=   None
      _UpperCAmelCase    			=   self.sp_model.serialized_model_proto()
      return state


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

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

      _UpperCAmelCase    			=   spm.SentencePieceProcessor(**self.sp_model_kwargs       )
      self.sp_model.LoadFromSerializedProto(self.sp_model_proto       )


    def   lowerCAmelCase_	(       self						:	Union[str, Any] ,					__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						:	Dict ,					__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						:	Union[str, Any]       ):
      return len(self.sp_model       ) + self.fairseq_offset + 1  # Add the <mask> token


    def   lowerCAmelCase_	(       self						:	Optional[int]       ):
      _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						:	Any ,					__lowerCAmelCase						:	str       ):
      return self.sp_model.encode(__lowerCAmelCase ,					out_type=__lowerCAmelCase       )


    def   lowerCAmelCase_	(       self						:	int ,					__lowerCAmelCase						:	Dict       ):
      if token in self.fairseq_tokens_to_ids:
        return self.fairseq_tokens_to_ids[token]
      _UpperCAmelCase    			=   self.sp_model.PieceToId(__lowerCAmelCase       )

      # Need to return unknown token if the SP model returned 0
      return spm_id + self.fairseq_offset if spm_id else self.unk_token_id


    def   lowerCAmelCase_	(       self						:	Optional[Any] ,					__lowerCAmelCase						:	List[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						:	List[str] ,					__lowerCAmelCase						:	Dict       ):
      _UpperCAmelCase    			=   """""".join(__lowerCAmelCase       ).replace(__lowerCAmelCase ,					""" """       ).strip()
      return out_string


    def   lowerCAmelCase_	(       self						:	List[Any] ,					__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"""


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


UpperCAmelCase__			=    logging.get_logger(__name__)

UpperCAmelCase__			=    {
    """google/realm-cc-news-pretrained-embedder""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-encoder""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-scorer""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-openqa""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/config.json"""
    ),
    """google/realm-orqa-nq-openqa""": """https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/config.json""",
    """google/realm-orqa-nq-reader""": """https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/config.json""",
    """google/realm-orqa-wq-openqa""": """https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/config.json""",
    """google/realm-orqa-wq-reader""": """https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/config.json""",
    # See all REALM models at https://huggingface.co/models?filter=realm
}


class 							a					(		lowerCAmelCase_ ):
    _snake_case  :	List[Any]  				=				'realm'


    def __init__(       self						:	List[Any] ,					__lowerCAmelCase						:	List[str]=3_0522 ,					__lowerCAmelCase						:	Tuple=768 ,					__lowerCAmelCase						:	List[Any]=128 ,					__lowerCAmelCase						:	Tuple=12 ,					__lowerCAmelCase						:	List[str]=12 ,					__lowerCAmelCase						:	Union[str, Any]=8 ,					__lowerCAmelCase						:	List[str]=3072 ,					__lowerCAmelCase						:	Union[str, Any]="gelu_new" ,					__lowerCAmelCase						:	str=0.1 ,					__lowerCAmelCase						:	Tuple=0.1 ,					__lowerCAmelCase						:	List[str]=512 ,					__lowerCAmelCase						:	Dict=2 ,					__lowerCAmelCase						:	List[Any]=0.02 ,					__lowerCAmelCase						:	Optional[int]=1e-1_2 ,					__lowerCAmelCase						:	Any=256 ,					__lowerCAmelCase						:	Union[str, Any]=10 ,					__lowerCAmelCase						:	Dict=1e-3 ,					__lowerCAmelCase						:	str=5 ,					__lowerCAmelCase						:	str=320 ,					__lowerCAmelCase						:	Tuple=1335_3718 ,					__lowerCAmelCase						:	Optional[Any]=5000 ,					__lowerCAmelCase						:	int=1 ,					__lowerCAmelCase						:	Dict=0 ,					__lowerCAmelCase						:	Any=2 ,					**__lowerCAmelCase						:	Optional[int] ,					):
      super().__init__(pad_token_id=__lowerCAmelCase ,					bos_token_id=__lowerCAmelCase ,					eos_token_id=__lowerCAmelCase ,					**__lowerCAmelCase       )

      # Common config
      _UpperCAmelCase    			=   vocab_size
      _UpperCAmelCase    			=   max_position_embeddings
      _UpperCAmelCase    			=   hidden_size
      _UpperCAmelCase    			=   retriever_proj_size
      _UpperCAmelCase    			=   num_hidden_layers
      _UpperCAmelCase    			=   num_attention_heads
      _UpperCAmelCase    			=   num_candidates
      _UpperCAmelCase    			=   intermediate_size
      _UpperCAmelCase    			=   hidden_act
      _UpperCAmelCase    			=   hidden_dropout_prob
      _UpperCAmelCase    			=   attention_probs_dropout_prob
      _UpperCAmelCase    			=   initializer_range
      _UpperCAmelCase    			=   type_vocab_size
      _UpperCAmelCase    			=   layer_norm_eps

      # Reader config
      _UpperCAmelCase    			=   span_hidden_size
      _UpperCAmelCase    			=   max_span_width
      _UpperCAmelCase    			=   reader_layer_norm_eps
      _UpperCAmelCase    			=   reader_beam_size
      _UpperCAmelCase    			=   reader_seq_len

      # Retrieval config
      _UpperCAmelCase    			=   num_block_records
      _UpperCAmelCase    			=   searcher_beam_size
