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
  
  
  lowercase__    :       Optional[Any]						=			'''none'''
  lowercase__    :       Any						=			'''none'''
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__							)  ->			int:
  							lowerCAmelCase				=	value.split(snake_case__							)
  							return len(snake_case__							) > 1 and any((len(snake_case__							) == 3 for x in split)							)
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__							)  ->			Any:
  							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'''							)
  							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(''','''     ,						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      SCREAMING_SNAKE_CASE_  (		snake_case__							)  ->			Optional[Any]:
  							if answer is None:
  														return None
  							try:
  														lowerCAmelCase				=	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()
  
  
  lowercase__    :       List[Any]						=			{
      '''text''': lambda x: x,
      '''real''': convert_to_float,
  }
  
  
  
  
  class      lowercase_						(						enum.Enum		):
  	UpperCAmelCase_						:      List[str]     =       0
  	UpperCAmelCase_						:      Dict     =       1
  	UpperCAmelCase_						:      Tuple     =       2
  	UpperCAmelCase_						:      List[str]     =       3
  	UpperCAmelCase_						:      List[Any]     =       4
  	UpperCAmelCase_						:      Dict     =       5
  
  
  
  
  class      lowercase_						(						enum.Enum		):
  	UpperCAmelCase_						:      Tuple     =       0
  	UpperCAmelCase_						:      List[Any]     =       1
  	UpperCAmelCase_						:      Dict     =       2
  
  
  
  
  @dataclasses.dataclass
  class      lowercase_						:
  	UpperCAmelCase_						:      Text
  	UpperCAmelCase_						:      _Operator
  	UpperCAmelCase_						:      Any
  lowercase__    :       str						=			re.compile(R'''\w+|[^\w\s]+''', re.UNICODE | re.MULTILINE | re.DOTALL)
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__							)  ->			List[str]:
  							return list(_TOKENIZER.findall(x.lower()							)							)
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__     ,						snake_case__							)  ->			Dict:
  							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      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__     ,						snake_case__							)  ->			Optional[Any]:
  							lowerCAmelCase				=	table['''types''']
  							return _TYPE_CONVERTER[types[column]](snake_case__							)
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__							)  ->			Any:
  							return isinstance(snake_case__     ,						snake_case__							)
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__     ,						snake_case__							)  ->			List[Any]:
  							for cond in conditions:
  														lowerCAmelCase				=	row[cond.column]
  
  														lowerCAmelCase				=	_parse_value(snake_case__     ,						cond.column     ,						cond.cmp_value							)
  
  														if _is_string(snake_case__							) and _is_string(snake_case__							):
  																					lowerCAmelCase				=	_normalize_for_match(snake_case__							)
  																					lowerCAmelCase				=	_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      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__     ,						snake_case__							)  ->			int:
  							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.
  							lowerCAmelCase				=	[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      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__							)  ->			Dict:
  							lowerCAmelCase				=	sql_query['''agg''']
  							if aggregation_op_index >= 3:
  														lowerCAmelCase				=	_Aggregation(snake_case__							)
  							else:
  														lowerCAmelCase				=	_Aggregation.NONE
  
  							lowerCAmelCase				=	sql_query['''sel''']
  							lowerCAmelCase				=	[
  							    _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''']							)
  							]
  
  							lowerCAmelCase				=	[]
  							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):
  														lowerCAmelCase				=	{2: min, 1: max}
  														lowerCAmelCase				=	[(table['''rows'''][i][j], index) for index, (i, j) in enumerate(snake_case__							)]
  														lowerCAmelCase				=	functools.reduce(operators[sql_query['''agg''']]     ,						snake_case__							)
  
  														lowerCAmelCase				=	[indices[reduced[1]]]
  														return ret, _Aggregation.NONE
  
  							return indices, aggregation_op
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__     ,						snake_case__							)  ->			List[str]:
  							if float_answer is not None:
  														return [str(snake_case__							)]
  							return [str(table['''real_rows'''][r][c]							) for r, c in answer_coordinates]
  
  
  
  
  
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__							)  ->			List:
  							lowerCAmelCase	,   lowerCAmelCase				=	_get_answer_coordinates(snake_case__     ,						snake_case__							)
  							lowerCAmelCase				=	_get_float_answer(snake_case__     ,						snake_case__     ,						snake_case__							)
  							lowerCAmelCase				=	_get_answer_text(snake_case__     ,						snake_case__     ,						snake_case__							)
  							# keep the original data the same with TaPas
  							if len(snake_case__							) == 0:
  														lowerCAmelCase				=	[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      lowercase_						(						UpperCamelCase_		):
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  	UpperCAmelCase_						:      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
  
  
  
  