
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


UpperCAmelCase     				=			'''none'''
UpperCAmelCase     				=			'''none'''






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE							):
	lowercase					  =   value.split(_lowerCamelCase							)
	return len(_lowerCamelCase							) > 1 and any((len(_lowerCamelCase							) == 3 for x in split)							)






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE							):





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

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






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE							):





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


UpperCAmelCase     				=			{
    '''text''': lambda x: x,
    '''real''': convert_to_float,
}







class 	A_       (      enum.Enum       ):




	'''simple docstring'''


	_UpperCamelCase					:					Dict										=	0
	_UpperCamelCase					:					Tuple										=	1
	_UpperCamelCase					:					int										=	2
	_UpperCamelCase					:					Optional[int]										=	3
	_UpperCamelCase					:					Tuple										=	4
	_UpperCamelCase					:					int										=	5







class 	A_       (      enum.Enum       ):




	'''simple docstring'''


	_UpperCamelCase					:					List[str]										=	0
	_UpperCamelCase					:					Union[str, Any]										=	1
	_UpperCamelCase					:					Any										=	2







@dataclasses.dataclass
class 	A_       :




	'''simple docstring'''


	_UpperCamelCase					:					Text
	_UpperCamelCase					:					_Operator
	_UpperCamelCase					:					Any




UpperCAmelCase     				=			re.compile(R'''\w+|[^\w\s]+''', re.UNICODE | re.MULTILINE | re.DOTALL)






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE							):
	return list(_TOKENIZER.findall(x.lower()							)							)






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE							):





	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_		(							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE							):
	lowercase					  =   table['types']
	return _TYPE_CONVERTER[types[column]](_lowerCamelCase							)






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE							):
	return isinstance(_lowerCamelCase			,							_lowerCamelCase							)






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE							):





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

		lowercase					  =   _parse_value(_lowerCamelCase			,							cond.column			,							cond.cmp_value							)

		if _is_string(_lowerCamelCase							) and _is_string(_lowerCamelCase							):
			lowercase					  =   _normalize_for_match(_lowerCamelCase							)
			lowercase					  =   _normalize_for_match(_lowerCamelCase							)

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

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






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE							):





	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(_lowerCamelCase							)							)

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

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






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE							):
	lowercase					  =   sql_query['agg']
	if aggregation_op_index >= 3:
		lowercase					  =   _Aggregation(_lowerCamelCase							)
	else:
		lowercase					  =   _Aggregation.NONE

	lowercase					  =   sql_query['sel']
	lowercase					  =   [
	    _Condition(_lowerCamelCase			,							_Operator(_lowerCamelCase							)			,							_lowerCamelCase							)
	    for column, operator, cmp_value in zip(
	        sql_query['conds']['column_index']			,							sql_query['conds']['operator_index']			,							sql_query['conds']['condition']							)
	]

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

	if not indices:
		return [], aggregation_op

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

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

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

	return indices, aggregation_op






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE							):





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






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE							):
	lowercase  , lowercase					  =   _get_answer_coordinates(_lowerCamelCase			,							_lowerCamelCase							)
	lowercase					  =   _get_float_answer(_lowerCamelCase			,							_lowerCamelCase			,							_lowerCamelCase							)
	lowercase					  =   _get_answer_text(_lowerCamelCase			,							_lowerCamelCase			,							_lowerCamelCase							)
	# keep the original data the same with TaPas
	if len(_lowerCamelCase							) == 0:
		lowercase					  =   [EMPTY_ANSWER]
	return answer_text



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase     				=			{
    '''configuration_dpr''': ['''DPR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DPRConfig'''],
    '''tokenization_dpr''': [
        '''DPRContextEncoderTokenizer''',
        '''DPRQuestionEncoderTokenizer''',
        '''DPRReaderOutput''',
        '''DPRReaderTokenizer''',
    ],
}


try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase     				=			[
	    '''DPRContextEncoderTokenizerFast''',
	    '''DPRQuestionEncoderTokenizerFast''',
	    '''DPRReaderTokenizerFast''',
	]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase     				=			[
	    '''DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''DPRContextEncoder''',
	    '''DPRPretrainedContextEncoder''',
	    '''DPRPreTrainedModel''',
	    '''DPRPretrainedQuestionEncoder''',
	    '''DPRPretrainedReader''',
	    '''DPRQuestionEncoder''',
	    '''DPRReader''',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase     				=			[
	    '''TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TFDPRContextEncoder''',
	    '''TFDPRPretrainedContextEncoder''',
	    '''TFDPRPretrainedQuestionEncoder''',
	    '''TFDPRPretrainedReader''',
	    '''TFDPRQuestionEncoder''',
	    '''TFDPRReader''',
	]


if TYPE_CHECKING:
	from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
	from .tokenization_dpr import (
	    DPRContextEncoderTokenizer,
	    DPRQuestionEncoderTokenizer,
	    DPRReaderOutput,
	    DPRReaderTokenizer,
	)

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_dpr_fast import (
		    DPRContextEncoderTokenizerFast,
		    DPRQuestionEncoderTokenizerFast,
		    DPRReaderTokenizerFast,
		)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_dpr import (
		    DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DPRContextEncoder,
		    DPRPretrainedContextEncoder,
		    DPRPreTrainedModel,
		    DPRPretrainedQuestionEncoder,
		    DPRPretrainedReader,
		    DPRQuestionEncoder,
		    DPRReader,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_dpr import (
		    TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFDPRContextEncoder,
		    TFDPRPretrainedContextEncoder,
		    TFDPRPretrainedQuestionEncoder,
		    TFDPRPretrainedReader,
		    TFDPRQuestionEncoder,
		    TFDPRReader,
		)

else:
	import sys

	UpperCAmelCase     				=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

