




import dataclasses
import enum
import functools
import math
import re

# The following script is adapted from the script of TaPas.
# Original: https://github.com/google-research/tapas/master/wikisql_utils.py
from typing import Any, List, Text


__SCREAMING_SNAKE_CASE    :   str       ="""none"""
__SCREAMING_SNAKE_CASE    :   Tuple       ="""none"""

def 			lowerCAmelCase_			(  lowerCamelCase:       int     ,				lowerCamelCase:       List[Any]						)					->			Tuple:


      '''simple docstring'''




      lowerCamelCase__        =				value.split(lowerCamelCase						)
      return len(lowerCamelCase						) > 1 and any((len(lowerCamelCase						) == 3 for x in split)						)

def 			lowerCAmelCase_			(  lowerCamelCase:       List[str]						)					->			int:


      '''simple docstring'''




      if isinstance(lowerCamelCase     ,				lowerCamelCase						):
            return value
      if isinstance(lowerCamelCase     ,				lowerCamelCase						):
            return float(lowerCamelCase						)
      if not isinstance(lowerCamelCase     ,				lowerCamelCase						):
            raise ValueError('Argument value is not a string. Can\'t parse it as float'						)
      lowerCamelCase__        =				value

      try:
            # Example: 1,000.7
            if "." in sanitized and "," in sanitized:
                  return float(sanitized.replace(','     ,				''						)						)
            # 1,000
            if "," in sanitized and _split_thousands(','     ,				lowerCamelCase						):
                  return float(sanitized.replace(','     ,				''						)						)
            # 5,5556
            if "," in sanitized and sanitized.count(','						) == 1 and not _split_thousands(','     ,				lowerCamelCase						):
                  return float(sanitized.replace(','     ,				'.'						)						)
            # 0.0.0.1
            if sanitized.count('.'						) > 1:
                  return float(sanitized.replace('.'     ,				''						)						)
            # 0,0,0,1
            if sanitized.count(','						) > 1:
                  return float(sanitized.replace(','     ,				''						)						)
            return float(lowerCamelCase						)
      except ValueError:
            # Avoid adding the sanitized value in the error message.
            raise ValueError('Unable to convert value to float'						)

def 			lowerCAmelCase_			(  lowerCamelCase:       str						)					->			Optional[Any]:


      '''simple docstring'''




      if answer is None:
            return None
      try:
            lowerCamelCase__        =				convert_to_float(lowerCamelCase						)
            if isinstance(lowerCamelCase     ,				lowerCamelCase						) and math.isnan(lowerCamelCase						):
                  return None
            return value
      except ValueError:
            return answer.lower()


__SCREAMING_SNAKE_CASE    :   Any       ={
    """text""": lambda x: x,
    """real""": convert_to_float,
}






class 			A			(		enum.Enum		):
     """simple docstring"""

     _snake_case:	List[str]     =0
     _snake_case:	Optional[int]     =1
     _snake_case:	int     =2
     _snake_case:	Tuple     =3
     _snake_case:	Dict     =4
     _snake_case:	Tuple     =5






class 			A			(		enum.Enum		):
     """simple docstring"""

     _snake_case:	Optional[int]     =0
     _snake_case:	List[str]     =1
     _snake_case:	str     =2






@dataclasses.dataclass
class 			A			:
     """simple docstring"""

     _snake_case:	Text
     _snake_case:	_Operator
     _snake_case:	Any
__SCREAMING_SNAKE_CASE    :   Any       =re.compile(R"""\w+|[^\w\s]+""", re.UNICODE | re.MULTILINE | re.DOTALL)

def 			lowerCAmelCase_			(  lowerCamelCase:       Optional[Any]						)					->			Optional[int]:


      '''simple docstring'''




      return list(_TOKENIZER.findall(x.lower()						)						)

def 			lowerCAmelCase_			(  lowerCamelCase:       str     ,				lowerCamelCase:       Union[str, Any]     ,				lowerCamelCase:       str						)					->			Union[str, Any]:


      '''simple docstring'''




      if operator == _Operator.EQUALS:
            return src == tgt
      elif operator == _Operator.GREATER:
            return src > tgt
      elif operator == _Operator.LESSER:
            return src < tgt
      raise ValueError(f"""Unknown operator: {operator}"""						)

def 			lowerCAmelCase_			(  lowerCamelCase:       Optional[int]     ,				lowerCamelCase:       List[Any]     ,				lowerCamelCase:       Dict						)					->			Dict:


      '''simple docstring'''




      lowerCamelCase__        =				table['types']
      return _TYPE_CONVERTER[types[column]](lowerCamelCase						)

def 			lowerCAmelCase_			(  lowerCamelCase:       Dict						)					->			Union[str, Any]:


      '''simple docstring'''




      return isinstance(lowerCamelCase     ,				lowerCamelCase						)

def 			lowerCAmelCase_			(  lowerCamelCase:       int     ,				lowerCamelCase:       List[str]     ,				lowerCamelCase:       Tuple						)					->			Optional[Any]:


      '''simple docstring'''




      for cond in conditions:
            lowerCamelCase__        =				row[cond.column]

            lowerCamelCase__        =				_parse_value(lowerCamelCase     ,				cond.column     ,				cond.cmp_value						)

            if _is_string(lowerCamelCase						) and _is_string(lowerCamelCase						):
                  lowerCamelCase__        =				_normalize_for_match(lowerCamelCase						)
                  lowerCamelCase__        =				_normalize_for_match(lowerCamelCase						)

            if not isinstance(lowerCamelCase     ,				type(lowerCamelCase						)						):
                  raise ValueError('Type difference {} != {}'.format(type(lowerCamelCase						)     ,				type(lowerCamelCase						)						)						)

            if not _compare(cond.operator     ,				lowerCamelCase     ,				lowerCamelCase						):
                  return False
      return True

def 			lowerCAmelCase_			(  lowerCamelCase:       Optional[int]     ,				lowerCamelCase:       Dict     ,				lowerCamelCase:       str						)					->			Dict:


      '''simple docstring'''




      if not answer_coordinates:
            if aggregation_op == _Aggregation.COUNT:
                  return 0.0
            else:
                  return EMPTY_ANSWER_AGG

    # Count can support non numeric answers.
      if aggregation_op == _Aggregation.COUNT:
            return float(len(lowerCamelCase						)						)

      # If we have just one answer, if float returns it or try a conversion.
      lowerCamelCase__        =				[table['rows'][i][j] for (i, j) in answer_coordinates]
      if len(lowerCamelCase						) == 1:
            try:
                  return convert_to_float(values[0]						)
            except ValueError as e:
                  if aggregation_op != _Aggregation.NONE:
                        raise e

      if aggregation_op == _Aggregation.NONE:
            return None

      # Other aggregation only support numeric values. Bail out if we have strings.
      if not all((isinstance(lowerCamelCase     ,				(int, float)						) for v in values)						):
            return None

      if aggregation_op == _Aggregation.SUM:
            return float(sum(lowerCamelCase						)						)
      elif aggregation_op == _Aggregation.AVERAGE:
            return sum(lowerCamelCase						) / len(lowerCamelCase						)
      else:
            raise ValueError(f"""Unknown aggregation: {aggregation_op}"""						)

def 			lowerCAmelCase_			(  lowerCamelCase:       Any     ,				lowerCamelCase:       List[Any]						)					->			Optional[int]:


      '''simple docstring'''




      lowerCamelCase__        =				sql_query['agg']
      if aggregation_op_index >= 3:
            lowerCamelCase__        =				_Aggregation(lowerCamelCase						)
      else:
            lowerCamelCase__        =				_Aggregation.NONE

      lowerCamelCase__        =				sql_query['sel']
      lowerCamelCase__        =				[
          _Condition(lowerCamelCase     ,				_Operator(lowerCamelCase						)     ,				lowerCamelCase						)
          for column, operator, cmp_value in zip(
              sql_query['conds']['column_index']     ,				sql_query['conds']['operator_index']     ,				sql_query['conds']['condition']						)
      ]

      lowerCamelCase__        =				[]
      for row in range(len(table['rows']						)						):
            if _respect_conditions(lowerCamelCase     ,				table['rows'][row]     ,				lowerCamelCase						):
                  indices.append((row, target_column)						)

      if not indices:
            return [], aggregation_op

      if len(lowerCamelCase						) == 1:
            return indices, aggregation_op

      # Parsing of MIN/MAX.
      if aggregation_op_index in (1, 2):
            lowerCamelCase__        =				{2: min, 1: max}
            lowerCamelCase__        =				[(table['rows'][i][j], index) for index, (i, j) in enumerate(lowerCamelCase						)]
            lowerCamelCase__        =				functools.reduce(operators[sql_query['agg']]     ,				lowerCamelCase						)

            lowerCamelCase__        =				[indices[reduced[1]]]
            return ret, _Aggregation.NONE

      return indices, aggregation_op

def 			lowerCAmelCase_			(  lowerCamelCase:       Tuple     ,				lowerCamelCase:       List[Any]     ,				lowerCamelCase:       List[str]						)					->			Dict:


      '''simple docstring'''




      if float_answer is not None:
            return [str(lowerCamelCase						)]
      return [str(table['real_rows'][r][c]						) for r, c in answer_coordinates]


def 			lowerCAmelCase_			(  lowerCamelCase:       Tuple     ,				lowerCamelCase:       List[Any]						)					->			List:


      '''simple docstring'''




      lowerCamelCase__  ,		lowerCamelCase__        =				_get_answer_coordinates(lowerCamelCase     ,				lowerCamelCase						)
      lowerCamelCase__        =				_get_float_answer(lowerCamelCase     ,				lowerCamelCase     ,				lowerCamelCase						)
      lowerCamelCase__        =				_get_answer_text(lowerCamelCase     ,				lowerCamelCase     ,				lowerCamelCase						)
      # keep the original data the same with TaPas
      if len(lowerCamelCase						) == 0:
            lowerCamelCase__        =				[EMPTY_ANSWER]
      return answer_text





import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_longformer import LongformerTokenizer


__SCREAMING_SNAKE_CASE    :   Dict       =logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE    :   str       ={"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

__SCREAMING_SNAKE_CASE    :   Dict       ={
    """vocab_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
    },
    """merges_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
    },
    """tokenizer_file""": {
        """allenai/longformer-base-4096""": (
            """https://huggingface.co/allenai/longformer-base-4096/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/tokenizer.json"""
        ),
    },
}

__SCREAMING_SNAKE_CASE    :   int       ={
    """allenai/longformer-base-4096""": 4_096,
    """allenai/longformer-large-4096""": 4_096,
    """allenai/longformer-large-4096-finetuned-triviaqa""": 4_096,
    """allenai/longformer-base-4096-extra.pos.embd.only""": 4_096,
    """allenai/longformer-large-4096-extra.pos.embd.only""": 4_096,
}






class 			A			(		_lowerCAmelCase		):
     """simple docstring"""

     _snake_case:	Optional[Any]     =VOCAB_FILES_NAMES
     _snake_case:	List[str]     =PRETRAINED_VOCAB_FILES_MAP
     _snake_case:	str     =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _snake_case:	str     =["input_ids", "attention_mask"]
     _snake_case:	Union[str, Any]     =LongformerTokenizer




     def __init__(    self  :   str	,  A__  :   Optional[Any]=None	,  A__  :   Dict=None	,  A__  :   Any=None	,  A__  :   Optional[Any]="replace"	,  A__  :   Tuple="<s>"	,  A__  :   Any="</s>"	,  A__  :   Dict="</s>"	,  A__  :   Any="<s>"	,  A__  :   Optional[Any]="<unk>"	,  A__  :   Tuple="<pad>"	,  A__  :   Union[str, Any]="<mask>"	,  A__  :   List[str]=False	,  A__  :   List[str]=True	,  **A__  :   Optional[int]	,  )				->       List[str]:
           super().__init__(
               A__	,  A__	,  tokenizer_file=A__	,  errors=A__	,  bos_token=A__	,  eos_token=A__	,  sep_token=A__	,  cls_token=A__	,  unk_token=A__	,  pad_token=A__	,  mask_token=A__	,  add_prefix_space=A__	,  trim_offsets=A__	,  **A__	,  )

           lowerCamelCase__        =				json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()			)
           if pre_tok_state.get('add_prefix_space'	,  A__			) != add_prefix_space:
                 lowerCamelCase__        =				getattr(A__	,  pre_tok_state.pop('type'			)			)
                 lowerCamelCase__        =				add_prefix_space
                 lowerCamelCase__        =				pre_tok_class(**A__			)

           lowerCamelCase__        =				add_prefix_space

           lowerCamelCase__        =				'post_processor'
           lowerCamelCase__        =				getattr(self.backend_tokenizer	,  A__	,  A__			)
           if tokenizer_component_instance:
                 lowerCamelCase__        =				json.loads(tokenizer_component_instance.__getstate__()			)

                 # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
                 if "sep" in state:
                       lowerCamelCase__        =				tuple(state['sep']			)
                 if "cls" in state:
                       lowerCamelCase__        =				tuple(state['cls']			)

                 lowerCamelCase__        =				False

                 if state.get('add_prefix_space'	,  A__			) != add_prefix_space:
                       lowerCamelCase__        =				add_prefix_space
                       lowerCamelCase__        =				True

                 if state.get('trim_offsets'	,  A__			) != trim_offsets:
                       lowerCamelCase__        =				trim_offsets
                       lowerCamelCase__        =				True

                 if changes_to_apply:
                       lowerCamelCase__        =				getattr(A__	,  state.pop('type'			)			)
                       lowerCamelCase__        =				component_class(**A__			)
                       setattr(self.backend_tokenizer	,  A__	,  A__			)




     @property
     def  __snake_case   (    self  :   Tuple			)				->       str:
           if self._mask_token is None:
                 if self.verbose:
                       logger.error('Using mask_token, but it is not set yet.'			)
                 return None
           return str(self._mask_token			)




     @mask_token.setter
     def  __snake_case   (    self  :   Dict	,  A__  :   Tuple			)				->       int:
           lowerCamelCase__        =				AddedToken(A__	,  lstrip=A__	,  rstrip=A__			) if isinstance(A__	,  A__			) else value
           lowerCamelCase__        =				value




     def  __snake_case   (    self  :   Any	,  *A__  :   Any	,  **A__  :   Any			)				->       BatchEncoding:
           lowerCamelCase__        =				kwargs.get('is_split_into_words'	,  A__			)
           assert self.add_prefix_space or not is_split_into_words, (
               F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
               "to use it with pretokenized inputs."
           )

           return super()._batch_encode_plus(*A__	,  **A__			)




     def  __snake_case   (    self  :   Tuple	,  *A__  :   str	,  **A__  :   int			)				->       BatchEncoding:
           lowerCamelCase__        =				kwargs.get('is_split_into_words'	,  A__			)

           assert self.add_prefix_space or not is_split_into_words, (
               F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
               "to use it with pretokenized inputs."
           )

           return super()._encode_plus(*A__	,  **A__			)




     def  __snake_case   (    self  :   Union[str, Any]	,  A__  :   str	,  A__  :   Optional[str] = None			)				->       Tuple[str]:
           lowerCamelCase__        =				self._tokenizer.model.save(A__	,  name=A__			)
           return tuple(A__			)




     def  __snake_case   (    self  :   Any	,  A__  :   int	,  A__  :   List[str]=None			)				->       Dict:
           lowerCamelCase__        =				[self.bos_token_id] + token_ids_a + [self.eos_token_id]
           if token_ids_a is None:
                 return output

           return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]




     def  __snake_case   (    self  :   Union[str, Any]	,  A__  :   List[int]	,  A__  :   Optional[List[int]] = None			)				->       List[int]:
           lowerCamelCase__        =				[self.sep_token_id]
           lowerCamelCase__        =				[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]