


"""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


__SCREAMING_SNAKE_CASE					=						"""none"""
__SCREAMING_SNAKE_CASE					=						"""none"""



def 						__a      (  a,		a					):





       """simple docstring"""







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



def 						__a      (  a					):





       """simple docstring"""







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

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



def 						__a      (  a					):





       """simple docstring"""







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


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





class __snake_case		(					enum.Enum      ):







   """simple docstring"""




   lowerCAmelCase_				:   int     	=			0
   lowerCAmelCase_				:   int     	=			1
   lowerCAmelCase_				:   Tuple     	=			2
   lowerCAmelCase_				:   str     	=			3
   lowerCAmelCase_				:   Union[str, Any]     	=			4
   lowerCAmelCase_				:   Optional[Any]     	=			5






class __snake_case		(					enum.Enum      ):







   """simple docstring"""




   lowerCAmelCase_				:   List[Any]     	=			0
   lowerCAmelCase_				:   List[str]     	=			1
   lowerCAmelCase_				:   Tuple     	=			2






@dataclasses.dataclass
class __snake_case		:







   """simple docstring"""




   lowerCAmelCase_				:   Text
   lowerCAmelCase_				:   _Operator
   lowerCAmelCase_				:   Any






__SCREAMING_SNAKE_CASE					=						re.compile(r"""\w+|[^\w\s]+""", re.UNICODE | re.MULTILINE | re.DOTALL)



def 						__a      (  a					):





       """simple docstring"""







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



def 						__a      (  a,		a,		a					):





       """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      (  a,		a,		a					):





       """simple docstring"""







       _a          =				table["types"]
       return _TYPE_CONVERTER[types[column]](a					)



def 						__a      (  a					):





       """simple docstring"""







       return isinstance(a,		a					)



def 						__a      (  a,		a,		a					):





       """simple docstring"""







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

              _a          =				_parse_value(a,		cond.column,		cond.cmp_value					)

              if _is_string(a					) and _is_string(a					):
                     _a          =				_normalize_for_match(a					)
                     _a          =				_normalize_for_match(a					)

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

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



def 						__a      (  a,		a,		a					):





       """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(a					)					)

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

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



def 						__a      (  a,		a					):





       """simple docstring"""







       _a          =				sql_query["agg"]
       if aggregation_op_index >= 3:
              _a          =				_Aggregation(a					)
       else:
              _a          =				_Aggregation.NONE

       _a          =				sql_query["sel"]
       _a          =				[
           _Condition(a,		_Operator(a					),		a					)
           for column, operator, cmp_value in zip(
               sql_query["conds"]["column_index"],		sql_query["conds"]["operator_index"],		sql_query["conds"]["condition"]					)
       ]

       _a          =				[]
       for row in range(len(table["rows"]					)					):
              if _respect_conditions(a,		table["rows"][row],		a					):
                     indices.append((row, target_column)					)

       if not indices:
              return [], aggregation_op

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

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

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

       return indices, aggregation_op



def 						__a      (  a,		a,		a					):





       """simple docstring"""







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



def 						__a      (  a,		a					):





       """simple docstring"""







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




"""simple docstring"""




import warnings

from ...utils import logging
from .image_processing_vit import ViTImageProcessor


__SCREAMING_SNAKE_CASE					=						logging.get_logger(__name__)





class __snake_case		(					_SCREAMING_SNAKE_CASE      ):







   """simple docstring"""




   def __init__(		self							:Tuple				,  *UpperCamelCase__							:Tuple				,  **UpperCamelCase__							:Any       ):
          warnings.warn(
              "The class ViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
              " use ViTImageProcessor instead."				,  UpperCamelCase__				,  )
          super().__init__(*UpperCamelCase__				,  **UpperCamelCase__       )
