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




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



