






"""simple docstring"""
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


snake_case   :   str    		=		"""none"""
snake_case   :   Any    		=		"""none"""


def        A	(							__snake_case:   List[str]   ,    __snake_case:   Dict     )						->		Dict:

       """simple docstring"""





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


def        A	(							__snake_case:   Dict     )						->		Optional[Any]:

       """simple docstring"""





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

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


def        A	(							__snake_case:   Any     )						->		str:

       """simple docstring"""





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


snake_case   :   int    		=		{
    """text""": lambda x: x,
    """real""": convert_to_float,
}



class 					UpperCamelCase__   (							enum.Enum):







    """simple docstring"""
    __UpperCAmelCase											=   0
    __UpperCAmelCase											=   1
    __UpperCAmelCase											=   2
    __UpperCAmelCase											=   3
    __UpperCAmelCase											=   4
    __UpperCAmelCase											=   5



class 					UpperCamelCase__   (							enum.Enum):







    """simple docstring"""
    __UpperCAmelCase											=   0
    __UpperCAmelCase											=   1
    __UpperCAmelCase											=   2



@dataclasses.dataclass
class 					UpperCamelCase__   :







    """simple docstring"""
    __UpperCAmelCase											=   42
    __UpperCAmelCase											=   42
    __UpperCAmelCase											=   42
snake_case   :   Optional[int]    		=		re.compile(r"""\w+|[^\w\s]+""", re.UNICODE | re.MULTILINE | re.DOTALL)


def        A	(							__snake_case:   Any     )						->		List[str]:

       """simple docstring"""





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


def        A	(							__snake_case:   int   ,    __snake_case:   Optional[int]   ,    __snake_case:   Dict     )						->		Dict:

       """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        A	(							__snake_case:   List[str]   ,    __snake_case:   Optional[int]   ,    __snake_case:   Tuple     )						->		Optional[Any]:

       """simple docstring"""





       __magic_name__										=						table['types']
       return _TYPE_CONVERTER[types[column]](__snake_case     )


def        A	(							__snake_case:   List[str]     )						->		Dict:

       """simple docstring"""





       return isinstance(__snake_case   ,    __snake_case     )


def        A	(							__snake_case:   List[Any]   ,    __snake_case:   Tuple   ,    __snake_case:   List[Any]     )						->		Optional[int]:

       """simple docstring"""





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

              __magic_name__										=						_parse_value(__snake_case   ,    cond.column   ,    cond.cmp_value     )

              if _is_string(__snake_case     ) and _is_string(__snake_case     ):
                     __magic_name__										=						_normalize_for_match(__snake_case     )
                     __magic_name__										=						_normalize_for_match(__snake_case     )

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

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


def        A	(							__snake_case:   str   ,    __snake_case:   Optional[int]   ,    __snake_case:   Optional[Any]     )						->		Optional[Any]:

       """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(__snake_case     )     )

       # If we have just one answer, if float returns it or try a conversion.
       __magic_name__										=						[table['rows'][i][j] for (i, j) in answer_coordinates]
       if len(__snake_case     ) == 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(__snake_case   ,    (int, float)     ) for v in values)     ):
              return None

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


def        A	(							__snake_case:   Dict   ,    __snake_case:   str     )						->		List[Any]:

       """simple docstring"""





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

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

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

       if not indices:
              return [], aggregation_op

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

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

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

       return indices, aggregation_op


def        A	(							__snake_case:   Optional[Any]   ,    __snake_case:   int   ,    __snake_case:   str     )						->		Any:

       """simple docstring"""





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






def        A	(							__snake_case:   Any   ,    __snake_case:   Optional[Any]     )						->		List:

       """simple docstring"""





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







"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


snake_case   :   Optional[int]    		=		{
    """configuration_splinter""": ["""SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SplinterConfig"""],
    """tokenization_splinter""": ["""SplinterTokenizer"""],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case   :   Dict    		=		["""SplinterTokenizerFast"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case   :   Dict    		=		[
     """SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """SplinterForQuestionAnswering""",
     """SplinterForPreTraining""",
     """SplinterLayer""",
     """SplinterModel""",
     """SplinterPreTrainedModel""",
 ]


if TYPE_CHECKING:
 from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
 from .tokenization_splinter import SplinterTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_splinter_fast import SplinterTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_splinter import (
      SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
      SplinterForPreTraining,
      SplinterForQuestionAnswering,
      SplinterLayer,
      SplinterModel,
      SplinterPreTrainedModel,
  )


else:
 import sys

 snake_case   :   List[str]    		=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)