





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer


__A									=				logging.get_logger(__name__)

__A									=				{"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

__A									=				{
    "vocab_file": {
        "yjernite/retribert-base-uncased": (
            "https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/vocab.txt"
        ),
    },
    "tokenizer_file": {
        "yjernite/retribert-base-uncased": (
            "https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/tokenizer.json"
        ),
    },
}

__A									=				{
    "yjernite/retribert-base-uncased": 512,
}


__A									=				{
    "yjernite/retribert-base-uncased": {"do_lower_case": True},
}



class    _SCREAMING_SNAKE_CASE						(	__SCREAMING_SNAKE_CASE    ):







 '''simple docstring'''
 lowercase_		=			VOCAB_FILES_NAMES
 lowercase_		=			PRETRAINED_VOCAB_FILES_MAP
 lowercase_		=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase_		=			PRETRAINED_INIT_CONFIGURATION
 lowercase_		=			RetriBertTokenizer
 lowercase_		=			["input_ids", "attention_mask"]

 def __init__(self				:   int       , UpperCAmelCase_				:   List[str]=None       , UpperCAmelCase_				:   str=None       , UpperCAmelCase_				:   Optional[Any]=True       , UpperCAmelCase_				:   Union[str, Any]="[UNK]"       , UpperCAmelCase_				:   Any="[SEP]"       , UpperCAmelCase_				:   List[str]="[PAD]"       , UpperCAmelCase_				:   Optional[Any]="[CLS]"       , UpperCAmelCase_				:   Optional[Any]="[MASK]"       , UpperCAmelCase_				:   Dict=True       , UpperCAmelCase_				:   str=None       , **UpperCAmelCase_				:   str       , )       ->List[Any]:



   '''simple docstring'''



   super().__init__(
       UpperCAmelCase_       , tokenizer_file=UpperCAmelCase_       , do_lower_case=UpperCAmelCase_       , unk_token=UpperCAmelCase_       , sep_token=UpperCAmelCase_       , pad_token=UpperCAmelCase_       , cls_token=UpperCAmelCase_       , mask_token=UpperCAmelCase_       , tokenize_chinese_chars=UpperCAmelCase_       , strip_accents=UpperCAmelCase_       , **UpperCAmelCase_       , )

   lowerCamelCase__:      List[Any]			  =json.loads(self.backend_tokenizer.normalizer.__getstate__())
   if (
       normalizer_state.get("lowercase"       , UpperCAmelCase_) != do_lower_case
       or normalizer_state.get("strip_accents"       , UpperCAmelCase_) != strip_accents
       or normalizer_state.get("handle_chinese_chars"       , UpperCAmelCase_) != tokenize_chinese_chars
   ):
     lowerCamelCase__:      Dict			  =getattr(UpperCAmelCase_       , normalizer_state.pop("type"))
     lowerCamelCase__:      int			  =do_lower_case
     lowerCamelCase__:      int			  =strip_accents
     lowerCamelCase__:      List[str]			  =tokenize_chinese_chars
     lowerCamelCase__:      Tuple			  =normalizer_class(**UpperCAmelCase_)

   lowerCamelCase__:      Any			  =do_lower_case

 def 							SCREAMING_SNAKE_CASE_					(self				:   List[str]       , UpperCAmelCase_				:   Dict       , UpperCAmelCase_				:   Optional[Any]=None)       ->List[str]:



   '''simple docstring'''



   lowerCamelCase__:      Optional[Any]			  =[self.cls_token_id] + token_ids_a + [self.sep_token_id]

   if token_ids_a:
     output += token_ids_a + [self.sep_token_id]

   return output

 def 							SCREAMING_SNAKE_CASE_					(self				:   Dict       , UpperCAmelCase_				:   List[int]       , UpperCAmelCase_				:   Optional[List[int]] = None)       ->List[int]:



   '''simple docstring'''



   lowerCamelCase__:      Tuple			  =[self.sep_token_id]
   lowerCamelCase__:      Optional[int]			  =[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) * [0] + len(token_ids_a + sep) * [1]







 def 							SCREAMING_SNAKE_CASE_					(self				:   Tuple       , UpperCAmelCase_				:   str       , UpperCAmelCase_				:   Optional[str] = None)       ->Tuple[str]:



   '''simple docstring'''



   lowerCamelCase__:      Tuple			  =self._tokenizer.model.save(UpperCAmelCase_       , name=UpperCAmelCase_)
   return tuple(UpperCAmelCase_)








from typing import Any





def      lowerCAmelCase_ (       __a	,    __a	,    __a	,    __a	,    __a	,    )     ->		list:







  """simple docstring"""





  _validation(
      __a	,    __a	,    __a	,    __a	,    __a	,    )
  # Creates data structures and fill initial step
  lowerCamelCase__:      dict			  ={}
  lowerCamelCase__:      dict			  ={}
  for state in states_space:
    lowerCamelCase__:      Optional[Any]			  =observations_space[0]
    lowerCamelCase__:      List[Any]			  =(
        initial_probabilities[state] * emission_probabilities[state][observation]
    )
    lowerCamelCase__:      int			  =None

  # Fills the data structure with the probabilities of
  # different transitions and pointers to previous states
  for o in range(1	,    len(__a		)		):
    lowerCamelCase__:      Tuple			  =observations_space[o]
    lowerCamelCase__:      Optional[Any]			  =observations_space[o - 1]
    for state in states_space:
      # Calculates the argmax for probability function
      lowerCamelCase__:      Tuple			  =""
      lowerCamelCase__:      Optional[Any]			  =-1
      for k_state in states_space:
        lowerCamelCase__:      int			  =(
            probabilities[(k_state, prior_observation)]
            * transition_probabilities[k_state][state]
            * emission_probabilities[state][observation]
        )
        if probability > max_probability:
          lowerCamelCase__:      List[str]			  =probability
          lowerCamelCase__:      int			  =k_state

            # Update probabilities and pointers dicts
      lowerCamelCase__:      Any			  =(
          probabilities[(arg_max, prior_observation)]
          * transition_probabilities[arg_max][state]
          * emission_probabilities[state][observation]
      )

      lowerCamelCase__:      int			  =arg_max

    # The final observation
  lowerCamelCase__:      Any			  =observations_space[len(__a		) - 1]

  # argmax for given final observation
  lowerCamelCase__:      Optional[Any]			  =""
  lowerCamelCase__:      int			  =-1
  for k_state in states_space:
    lowerCamelCase__:      Tuple			  =probabilities[(k_state, final_observation)]
    if probability > max_probability:
      lowerCamelCase__:      List[Any]			  =probability
      lowerCamelCase__:      Dict			  =k_state
  lowerCamelCase__:      str			  =arg_max

  # Process pointers backwards
  lowerCamelCase__:      Union[str, Any]			  =last_state
  lowerCamelCase__:      List[str]			  =[]
  for o in range(len(__a		) - 1	,    -1	,    -1		):
    result.append(__a		)
    lowerCamelCase__:      Union[str, Any]			  =pointers[previous, observations_space[o]]
  result.reverse()

  return result





def      lowerCAmelCase_ (       __a	,    __a	,    __a	,    __a	,    __a	,    )     ->		None:







  """simple docstring"""





  _validate_not_empty(
      __a	,    __a	,    __a	,    __a	,    __a	,    )
  _validate_lists(__a	,    __a		)
  _validate_dicts(
      __a	,    __a	,    __a		)





def      lowerCAmelCase_ (       __a	,    __a	,    __a	,    __a	,    __a	,    )     ->		None:







  """simple docstring"""





  if not all(
      [
          observations_space,
          states_space,
          initial_probabilities,
          transition_probabilities,
          emission_probabilities,
      ]		):
    raise ValueError("There's an empty parameter"		)





def      lowerCAmelCase_ (       __a	,    __a		)     ->		None:







  """simple docstring"""





  _validate_list(__a	,    "observations_space"		)
  _validate_list(__a	,    "states_space"		)





def      lowerCAmelCase_ (       __a	,    __a		)     ->		None:







  """simple docstring"""





  if not isinstance(_object	,    __a		):
    lowerCamelCase__:      Tuple			  =F"""{var_name} must be a list"""
    raise ValueError(__a		)
  else:
    for x in _object:
      if not isinstance(__a	,    __a		):
        lowerCamelCase__:      str			  =F"""{var_name} must be a list of strings"""
        raise ValueError(__a		)





def      lowerCAmelCase_ (       __a	,    __a	,    __a	,    )     ->		None:







  """simple docstring"""





  _validate_dict(__a	,    "initial_probabilities"	,    __a		)
  _validate_nested_dict(__a	,    "transition_probabilities"		)
  _validate_nested_dict(__a	,    "emission_probabilities"		)





def      lowerCAmelCase_ (       __a	,    __a		)     ->		None:







  """simple docstring"""





  _validate_dict(_object	,    __a	,    __a		)
  for x in _object.values():
    _validate_dict(__a	,    __a	,    __a	,    __a		)





def      lowerCAmelCase_ (       __a	,    __a	,    __a	,    __a = False		)     ->		None:







  """simple docstring"""





  if not isinstance(_object	,    __a		):
    lowerCamelCase__:      Optional[int]			  =F"""{var_name} must be a dict"""
    raise ValueError(__a		)
  if not all(isinstance(__a	,    __a		) for x in _object		):
    lowerCamelCase__:      Tuple			  =F"""{var_name} all keys must be strings"""
    raise ValueError(__a		)
  if not all(isinstance(__a	,    __a		) for x in _object.values()		):
    lowerCamelCase__:      Dict			  ="nested dictionary " if nested else ""
    lowerCamelCase__:      List[str]			  =F"""{var_name} {nested_text}all values must be {value_type.__name__}"""
    raise ValueError(__a		)


if __name__ == "__main__":
     from doctest import testmod

     testmod()

