code: 
  
  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_    						=				'''none'''
  snake_case_    						=				'''none'''
  
  
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Optional[int]			,  SCREAMING_SNAKE_CASE_	:					Dict    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       lowercase__					:     List[str]   = value.split(SCREAMING_SNAKE_CASE_    )
       return len(SCREAMING_SNAKE_CASE_    ) > 1 and any((len(SCREAMING_SNAKE_CASE_    ) == 3 for x in split)    )
  
  
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Optional[Any]    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       if isinstance(SCREAMING_SNAKE_CASE_			,  SCREAMING_SNAKE_CASE_    ):
            return value
       if isinstance(SCREAMING_SNAKE_CASE_			,  SCREAMING_SNAKE_CASE_    ):
            return float(SCREAMING_SNAKE_CASE_    )
       if not isinstance(SCREAMING_SNAKE_CASE_			,  SCREAMING_SNAKE_CASE_    ):
            raise ValueError('Argument value is not a string. Can\'t parse it as float'    )
       lowercase__					:     Optional[int]   = value
  
       try:
            # Example: 1,000.7
            if "." in sanitized and "," in sanitized:
                 return float(sanitized.replace(','			,  ''    )    )
            # 1,000
            if "," in sanitized and _split_thousands(','			,  SCREAMING_SNAKE_CASE_    ):
                 return float(sanitized.replace(','			,  ''    )    )
            # 5,5556
            if "," in sanitized and sanitized.count(','    ) == 1 and not _split_thousands(','			,  SCREAMING_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(SCREAMING_SNAKE_CASE_    )
       except ValueError:
            # Avoid adding the sanitized value in the error message.
            raise ValueError('Unable to convert value to float'    )
  
  
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Any    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       if answer is None:
            return None
       try:
            lowercase__					:     List[Any]   = convert_to_float(SCREAMING_SNAKE_CASE_    )
            if isinstance(SCREAMING_SNAKE_CASE_			,  SCREAMING_SNAKE_CASE_    ) and math.isnan(SCREAMING_SNAKE_CASE_    ):
                 return None
            return value
       except ValueError:
            return answer.lower()
  
  
  snake_case_    						=				{
      '''text''': lambda x: x,
      '''real''': convert_to_float,
  }
  
  
  class    SCREAMING_SNAKE_CASE__      (enum.Enum  ):
      __lowerCamelCase		: Any														=  0
      __lowerCamelCase		: str														=  1
      __lowerCamelCase		: int														=  2
      __lowerCamelCase		: List[str]														=  3
      __lowerCamelCase		: List[str]														=  4
      __lowerCamelCase		: Tuple														=  5
  
  
  
  class    SCREAMING_SNAKE_CASE__      (enum.Enum  ):
      __lowerCamelCase		: int														=  0
      __lowerCamelCase		: Optional[int]														=  1
      __lowerCamelCase		: Optional[Any]														=  2
  
  
  
  @dataclasses.dataclass
  class    SCREAMING_SNAKE_CASE__      :
      __lowerCamelCase		: Text
      __lowerCamelCase		: _Operator
      __lowerCamelCase		: Any
  
  
  
  snake_case_    						=				re.compile(r'''\w+|[^\w\s]+''', re.UNICODE | re.MULTILINE | re.DOTALL)
  
  
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Optional[int]    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       return list(_TOKENIZER.findall(x.lower()    )    )
  
  
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					int			,  SCREAMING_SNAKE_CASE_	:					str			,  SCREAMING_SNAKE_CASE_	:					Tuple    ):
  
  
  
       '''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 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Optional[int]			,  SCREAMING_SNAKE_CASE_	:					Optional[int]			,  SCREAMING_SNAKE_CASE_	:					str    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       lowercase__					:     Tuple   = table['types']
       return _TYPE_CONVERTER[types[column]](SCREAMING_SNAKE_CASE_    )
  
  
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Optional[Any]    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       return isinstance(SCREAMING_SNAKE_CASE_			,  SCREAMING_SNAKE_CASE_    )
  
  
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Any			,  SCREAMING_SNAKE_CASE_	:					Any			,  SCREAMING_SNAKE_CASE_	:					List[Any]    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       for cond in conditions:
            lowercase__					:     List[str]   = row[cond.column]
  
            lowercase__					:     List[str]   = _parse_value(SCREAMING_SNAKE_CASE_			,  cond.column			,  cond.cmp_value    )
  
            if _is_string(SCREAMING_SNAKE_CASE_    ) and _is_string(SCREAMING_SNAKE_CASE_    ):
                 lowercase__					:     Union[str, Any]   = _normalize_for_match(SCREAMING_SNAKE_CASE_    )
                 lowercase__					:     str   = _normalize_for_match(SCREAMING_SNAKE_CASE_    )
  
            if not isinstance(SCREAMING_SNAKE_CASE_			,  type(SCREAMING_SNAKE_CASE_    )    ):
                 raise ValueError('Type difference {} != {}'.format(type(SCREAMING_SNAKE_CASE_    )			,  type(SCREAMING_SNAKE_CASE_    )    )    )
  
            if not _compare(cond.operator			,  SCREAMING_SNAKE_CASE_			,  SCREAMING_SNAKE_CASE_    ):
                 return False
       return True
  
  
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					List[Any]			,  SCREAMING_SNAKE_CASE_	:					List[Any]			,  SCREAMING_SNAKE_CASE_	:					Optional[int]    ):
  
  
  
       '''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(SCREAMING_SNAKE_CASE_    )    )
  
       # If we have just one answer, if float returns it or try a conversion.
       lowercase__					:     Optional[Any]   = [table['rows'][i][j] for (i, j) in answer_coordinates]
       if len(SCREAMING_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(SCREAMING_SNAKE_CASE_			,  (int, float)    ) for v in values)    ):
            return None
  
       if aggregation_op == _Aggregation.SUM:
            return float(sum(SCREAMING_SNAKE_CASE_    )    )
       elif aggregation_op == _Aggregation.AVERAGE:
            return sum(SCREAMING_SNAKE_CASE_    ) / len(SCREAMING_SNAKE_CASE_    )
       else:
            raise ValueError(f"""Unknown aggregation: {aggregation_op}"""    )
  
  
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Union[str, Any]			,  SCREAMING_SNAKE_CASE_	:					Union[str, Any]    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       lowercase__					:     Union[str, Any]   = sql_query['agg']
       if aggregation_op_index >= 3:
            lowercase__					:     Tuple   = _Aggregation(SCREAMING_SNAKE_CASE_    )
       else:
            lowercase__					:     str   = _Aggregation.NONE
  
       lowercase__					:     Optional[Any]   = sql_query['sel']
       lowercase__					:     int   = [
           _Condition(SCREAMING_SNAKE_CASE_			,  _Operator(SCREAMING_SNAKE_CASE_    )			,  SCREAMING_SNAKE_CASE_    )
           for column, operator, cmp_value in zip(
               sql_query['conds']['column_index']			,  sql_query['conds']['operator_index']			,  sql_query['conds']['condition']    )
       ]
  
       lowercase__					:     Optional[Any]   = []
       for row in range(len(table['rows']    )    ):
            if _respect_conditions(SCREAMING_SNAKE_CASE_			,  table['rows'][row]			,  SCREAMING_SNAKE_CASE_    ):
                 indices.append((row, target_column)    )
  
       if not indices:
            return [], aggregation_op
  
       if len(SCREAMING_SNAKE_CASE_    ) == 1:
            return indices, aggregation_op
  
       # Parsing of MIN/MAX.
       if aggregation_op_index in (1, 2):
            lowercase__					:     List[Any]   = {2: min, 1: max}
            lowercase__					:     int   = [(table['rows'][i][j], index) for index, (i, j) in enumerate(SCREAMING_SNAKE_CASE_    )]
            lowercase__					:     Union[str, Any]   = functools.reduce(operators[sql_query['agg']]			,  SCREAMING_SNAKE_CASE_    )
  
            lowercase__					:     str   = [indices[reduced[1]]]
            return ret, _Aggregation.NONE
  
       return indices, aggregation_op
  
  
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					str			,  SCREAMING_SNAKE_CASE_	:					List[Any]			,  SCREAMING_SNAKE_CASE_	:					Tuple    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       if float_answer is not None:
            return [str(SCREAMING_SNAKE_CASE_    )]
       return [str(table['real_rows'][r][c]    ) for r, c in answer_coordinates]
  
  
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Union[str, Any]			,  SCREAMING_SNAKE_CASE_	:					List[str]    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       lowercase__   ,				lowercase__					:     str   = _get_answer_coordinates(SCREAMING_SNAKE_CASE_			,  SCREAMING_SNAKE_CASE_    )
       lowercase__					:     List[str]   = _get_float_answer(SCREAMING_SNAKE_CASE_			,  SCREAMING_SNAKE_CASE_			,  SCREAMING_SNAKE_CASE_    )
       lowercase__					:     Optional[int]   = _get_answer_text(SCREAMING_SNAKE_CASE_			,  SCREAMING_SNAKE_CASE_			,  SCREAMING_SNAKE_CASE_    )
       # keep the original data the same with TaPas
       if len(SCREAMING_SNAKE_CASE_    ) == 0:
            lowercase__					:     Tuple   = [EMPTY_ANSWER]
       return answer_text
  
  
style_context: 
  
  from dataclasses import dataclass
  from typing import List, Optional, Union
  
  import numpy as np
  import PIL
  
  from ...utils import BaseOutput, is_invisible_watermark_available, is_torch_available, is_transformers_available
  
  
  @dataclass
  class    SCREAMING_SNAKE_CASE__      (__snake_case  ):
      __lowerCamelCase		: Union[List[PIL.Image.Image], np.ndarray]
  
  
  if is_transformers_available() and is_torch_available() and is_invisible_watermark_available():
         from .pipeline_stable_diffusion_xl import StableDiffusionXLPipeline
         from .pipeline_stable_diffusion_xl_imgaimg import StableDiffusionXLImgaImgPipeline
  
  