






"""simple docstring"""





from functools import partial
from typing import Any, Callable, Dict, List, Type, TypeVar, Union, overload

import torch
import torch.nn as nn
import torch.types






def 							A(    snake_case_		,  snake_case_		,  snake_case_						):
       """simple docstring"""





       if not inplace:
              lowercase__:							Optional[int]         =     ma + ma
       else:
              ma += ma

       return ma






def 							A(    snake_case_		,  snake_case_						):
       """simple docstring"""





       lowercase__:							str         =     -1 * len(snake_case_						)
       lowercase__:							int         =     list(range(len(tensor.shape[:zero_index]						)						)						)
       return tensor.permute(first_inds + [zero_index + i for i in inds]						)






def 							A(    snake_case_		,  snake_case_						):
       """simple docstring"""





       return t.reshape(t.shape[:-no_dims] + (-1,)						)






def 							A(    snake_case_		,  snake_case_		,  snake_case_		,  snake_case_ = 1E-4						):
       """simple docstring"""





       lowercase__:							List[Any]         =     mask.expand(*value.shape						)
       return torch.sum(mask * value		,  dim=snake_case_						) / (eps + torch.sum(snake_case_		,  dim=snake_case_						))






def 							A(    snake_case_		,  snake_case_ = 2.31_25		,  snake_case_ = 21.68_75		,  snake_case_ = 64						):
       """simple docstring"""





       lowercase__:							Tuple         =     torch.linspace(snake_case_		,  snake_case_		,  no_bins - 1		,  device=pts.device						)
       lowercase__:							Dict         =     torch.sqrt(torch.sum((pts.unsqueeze(-2						) - pts.unsqueeze(-3						)) ** 2		,  dim=-1						)						)
       return torch.bucketize(snake_case_		,  snake_case_						)






def 							A(    snake_case_		,  snake_case_						):
       """simple docstring"""





       lowercase__:							Optional[Any]         =     dicts[0]
       lowercase__:							Optional[int]         =     {}
       for k, v in first.items():
              lowercase__:							Optional[int]         =     [d[k] for d in dicts]
              if isinstance(snake_case_		,  snake_case_						):
                     lowercase__:							Optional[Any]         =     dict_multimap(snake_case_		,  snake_case_						)
              else:
                     lowercase__:							List[str]         =     fn(snake_case_						)

       return new_dict






def 							A(    snake_case_		,  snake_case_						):
       """simple docstring"""





       lowercase__:							Optional[Any]         =     v_bins.view(((1,) * len(x.shape						)) + (len(snake_case_						),)						)
       lowercase__:							List[str]         =     x[..., None] - reshaped_bins
       lowercase__:							Optional[int]         =     torch.argmin(torch.abs(snake_case_						)		,  dim=-1						)
       return nn.functional.one_hot(snake_case_		,  num_classes=len(snake_case_						)						).float()






def 							A(    snake_case_		,  snake_case_		,  snake_case_ = 0		,  snake_case_ = 0						):
       """simple docstring"""





       lowercase__:							List[Union[slice, torch.Tensor]]         =     []
       for i, s in enumerate(data.shape[:no_batch_dims]						):
              lowercase__:							Optional[Any]         =     torch.arange(snake_case_						)
              lowercase__:							Any         =     r.view(*(*((1,) * i), -1, *((1,) * (len(inds.shape						) - i - 1)))						)
              ranges.append(snake_case_						)

       lowercase__:							List[Union[slice, torch.Tensor]]         =     [slice(snake_case_						) for _ in range(len(data.shape						) - no_batch_dims						)]
       lowercase__:							Dict         =     inds
       ranges.extend(snake_case_						)
       # Matt note: Editing this to get around the behaviour of using a list as an array index changing
       # in recent Numpy versions
       return data[tuple(snake_case_						)]


UpperCamelCase					=     TypeVar("""T""")






def 							A(    snake_case_		,  snake_case_		,  snake_case_						):
       """simple docstring"""





       lowercase__:							Dict[Any, Union[dict, list, tuple, Any]]         =     {}
       for k, v in dic.items():
              if isinstance(snake_case_		,  snake_case_						):
                     lowercase__:							Optional[Any]         =     dict_map(snake_case_		,  snake_case_		,  snake_case_						)
              else:
                     lowercase__:							Union[str, Any]         =     tree_map(snake_case_		,  snake_case_		,  snake_case_						)

       return new_dict






@overload
def 							A(    snake_case_		,  snake_case_		,  snake_case_						):
       """simple docstring"""





       ...






@overload
def 							A(    snake_case_		,  snake_case_		,  snake_case_						):
       """simple docstring"""





       ...






@overload
def 							A(    snake_case_		,  snake_case_		,  snake_case_						):
       """simple docstring"""





       ...






@overload
def 							A(    snake_case_		,  snake_case_		,  snake_case_						):
       """simple docstring"""





       ...






def 							A(    snake_case_		,  snake_case_		,  snake_case_						):
       """simple docstring"""





       if isinstance(snake_case_		,  snake_case_						):
              return dict_map(snake_case_		,  snake_case_		,  snake_case_						)
       elif isinstance(snake_case_		,  snake_case_						):
              return [tree_map(snake_case_		,  snake_case_		,  snake_case_						) for x in tree]
       elif isinstance(snake_case_		,  snake_case_						):
              return tuple(tree_map(snake_case_		,  snake_case_		,  snake_case_						) for x in tree						)
       elif isinstance(snake_case_		,  snake_case_						):
              return fn(snake_case_						)
       else:
              print(type(snake_case_						)						)
              raise ValueError("Not supported"						)







UpperCamelCase					=     partial(tree_map, leaf_type=torch.Tensor)







"""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


_a	:	List[Any]=					"none"
_a	:	List[str]=					"none"
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Optional[int]     ,				UpperCAmelCase_       :							Tuple    )				->     Dict:

	'''simple docstring'''





	__snake_case     :				int 						=					value.split(UpperCAmelCase_    )
	return len(UpperCAmelCase_    ) > 1 and any((len(UpperCAmelCase_    ) == 3 for x in split)    )
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Optional[Any]    )				->     Tuple:

	'''simple docstring'''





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

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

	'''simple docstring'''





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


_a	:	Union[str, Any]=					{
    "text": lambda x: x,
    "real": convert_to_float,
}

class 						UpperCamelCase     (       enum.Enum		):
				UpperCAmelCase							: int       =						0
				UpperCAmelCase							: Optional[Any]       =						1
				UpperCAmelCase							: List[Any]       =						2
				UpperCAmelCase							: Dict       =						3
				UpperCAmelCase							: Union[str, Any]       =						4
				UpperCAmelCase							: int       =						5







class 						UpperCamelCase     (       enum.Enum		):
				UpperCAmelCase							: List[str]       =						0
				UpperCAmelCase							: List[str]       =						1
				UpperCAmelCase							: int       =						2







@dataclasses.dataclass
class 						UpperCamelCase     :
				UpperCAmelCase							: Text
				UpperCAmelCase							: _Operator
				UpperCAmelCase							: Any







_a	:	Union[str, Any]=					re.compile(R"\w+|[^\w\s]+", re.UNICODE | re.MULTILINE | re.DOTALL)
def     __UpperCAmelCase							(       UpperCAmelCase_       :							List[str]    )				->     Optional[Any]:

	'''simple docstring'''





	return list(_TOKENIZER.findall(x.lower()    )    )
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Tuple     ,				UpperCAmelCase_       :							int     ,				UpperCAmelCase_       :							List[Any]    )				->     List[str]:

	'''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     __UpperCAmelCase							(       UpperCAmelCase_       :							List[Any]     ,				UpperCAmelCase_       :							int     ,				UpperCAmelCase_       :							Optional[Any]    )				->     Dict:

	'''simple docstring'''





	__snake_case     :				Optional[Any] 						=					table['types']
	return _TYPE_CONVERTER[types[column]](UpperCAmelCase_    )
def     __UpperCAmelCase							(       UpperCAmelCase_       :							List[Any]    )				->     str:

	'''simple docstring'''





	return isinstance(UpperCAmelCase_     ,				UpperCAmelCase_    )
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Dict     ,				UpperCAmelCase_       :							Union[str, Any]     ,				UpperCAmelCase_       :							int    )				->     List[Any]:

	'''simple docstring'''





	for cond in conditions:
		__snake_case     :				Any 						=					row[cond.column]

		__snake_case     :				Tuple 						=					_parse_value(UpperCAmelCase_     ,				cond.column     ,				cond.cmp_value    )

		if _is_string(UpperCAmelCase_    ) and _is_string(UpperCAmelCase_    ):
			__snake_case     :				str 						=					_normalize_for_match(UpperCAmelCase_    )
			__snake_case     :				Dict 						=					_normalize_for_match(UpperCAmelCase_    )

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

		if not _compare(cond.operator     ,				UpperCAmelCase_     ,				UpperCAmelCase_    ):
			return False
	return True
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Union[str, Any]     ,				UpperCAmelCase_       :							List[str]     ,				UpperCAmelCase_       :							Optional[int]    )				->     Dict:

	'''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(UpperCAmelCase_    )    )

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

	if aggregation_op == _Aggregation.SUM:
		return float(sum(UpperCAmelCase_    )    )
	elif aggregation_op == _Aggregation.AVERAGE:
		return sum(UpperCAmelCase_    ) / len(UpperCAmelCase_    )
	else:
		raise ValueError(F"Unknown aggregation: {aggregation_op}"    )
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Optional[Any]     ,				UpperCAmelCase_       :							int    )				->     str:

	'''simple docstring'''





	__snake_case     :				int 						=					sql_query['agg']
	if aggregation_op_index >= 3:
		__snake_case     :				Optional[Any] 						=					_Aggregation(UpperCAmelCase_    )
	else:
		__snake_case     :				Any 						=					_Aggregation.NONE

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

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

	if not indices:
		return [], aggregation_op

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

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

		__snake_case     :				str 						=					[indices[reduced[1]]]
		return ret, _Aggregation.NONE

	return indices, aggregation_op
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Dict     ,				UpperCAmelCase_       :							List[Any]     ,				UpperCAmelCase_       :							Any    )				->     Optional[Any]:

	'''simple docstring'''





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

def     __UpperCAmelCase							(       UpperCAmelCase_       :							int     ,				UpperCAmelCase_       :							Tuple    )				->     List:

	'''simple docstring'''





	__snake_case						,							__snake_case     :				List[Any] 						=					_get_answer_coordinates(UpperCAmelCase_     ,				UpperCAmelCase_    )
	__snake_case     :				Optional[int] 						=					_get_float_answer(UpperCAmelCase_     ,				UpperCAmelCase_     ,				UpperCAmelCase_    )
	__snake_case     :				Union[str, Any] 						=					_get_answer_text(UpperCAmelCase_     ,				UpperCAmelCase_     ,				UpperCAmelCase_    )
	# keep the original data the same with TaPas
	if len(UpperCAmelCase_    ) == 0:
		__snake_case     :				List[str] 						=					[EMPTY_ANSWER]
	return answer_text





