

"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__A     :    int    =		{
    'configuration_nystromformer': ['NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NystromformerConfig'],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A     :    str    =		[
	    'NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'NystromformerForMaskedLM',
	    'NystromformerForMultipleChoice',
	    'NystromformerForQuestionAnswering',
	    'NystromformerForSequenceClassification',
	    'NystromformerForTokenClassification',
	    'NystromformerLayer',
	    'NystromformerModel',
	    'NystromformerPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_nystromformer import (
		    NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    NystromformerForMaskedLM,
		    NystromformerForMultipleChoice,
		    NystromformerForQuestionAnswering,
		    NystromformerForSequenceClassification,
		    NystromformerForTokenClassification,
		    NystromformerLayer,
		    NystromformerModel,
		    NystromformerPreTrainedModel,
		)


else:
	import sys

	__A     :    Union[str, Any]    =		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








"""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     :    int    =		'none'
__A     :    List[Any]    =		'none'
def    __SCREAMING_SNAKE_CASE						(						lowercase__			,							lowercase__      ):
					"""simple docstring"""
					A			=					value.split(lowercase__      )
					return len(lowercase__      ) > 1 and any((len(lowercase__      ) == 3 for x in split)      )
def    __SCREAMING_SNAKE_CASE						(						lowercase__      ):
					"""simple docstring"""
					if isinstance(lowercase__			,							lowercase__      ):
										return value
					if isinstance(lowercase__			,							lowercase__      ):
										return float(lowercase__      )
					if not isinstance(lowercase__			,							lowercase__      ):
										raise ValueError("Argument value is not a string. Can't parse it as float"      )
					A			=					value

					try:
										# Example: 1,000.7
										if "." in sanitized and "," in sanitized:
															return float(sanitized.replace(","			,							""      )      )
										# 1,000
										if "," in sanitized and _split_thousands(","			,							lowercase__      ):
															return float(sanitized.replace(","			,							""      )      )
										# 5,5556
										if "," in sanitized and sanitized.count(","      ) == 1 and not _split_thousands(","			,							lowercase__      ):
															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(lowercase__      )
					except ValueError:
										# Avoid adding the sanitized value in the error message.
										raise ValueError("Unable to convert value to float"      )
def    __SCREAMING_SNAKE_CASE						(						lowercase__      ):
					"""simple docstring"""
					if answer is None:
										return None
					try:
										A			=					convert_to_float(lowercase__      )
										if isinstance(lowercase__			,							lowercase__      ) and math.isnan(lowercase__      ):
															return None
										return value
					except ValueError:
										return answer.lower()


__A     :    List[str]    =		{
    'text': lambda x: x,
    'real': convert_to_float,
}





class 			__UpperCamelCase (   enum.Enum						):
		SCREAMING_SNAKE_CASE								=    0
		SCREAMING_SNAKE_CASE								=    1
		SCREAMING_SNAKE_CASE								=    2
		SCREAMING_SNAKE_CASE								=    3
		SCREAMING_SNAKE_CASE								=    4
		SCREAMING_SNAKE_CASE								=    5





class 			__UpperCamelCase (   enum.Enum						):
		SCREAMING_SNAKE_CASE								=    0
		SCREAMING_SNAKE_CASE								=    1
		SCREAMING_SNAKE_CASE								=    2





@dataclasses.dataclass
class 			__UpperCamelCase :
		SCREAMING_SNAKE_CASE								=    42
		SCREAMING_SNAKE_CASE								=    42
		SCREAMING_SNAKE_CASE								=    42

__A     :    int    =		re.compile(R'\w+|[^\w\s]+', re.UNICODE | re.MULTILINE | re.DOTALL)
def    __SCREAMING_SNAKE_CASE						(						lowercase__      ):
					"""simple docstring"""
					return list(_TOKENIZER.findall(x.lower()      )      )
def    __SCREAMING_SNAKE_CASE						(						lowercase__			,							lowercase__			,							lowercase__      ):
					"""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    __SCREAMING_SNAKE_CASE						(						lowercase__			,							lowercase__			,							lowercase__      ):
					"""simple docstring"""
					A			=					table["types"]
					return _TYPE_CONVERTER[types[column]](lowercase__      )
def    __SCREAMING_SNAKE_CASE						(						lowercase__      ):
					"""simple docstring"""
					return isinstance(lowercase__			,							lowercase__      )
def    __SCREAMING_SNAKE_CASE						(						lowercase__			,							lowercase__			,							lowercase__      ):
					"""simple docstring"""
					for cond in conditions:
										A			=					row[cond.column]

										A			=					_parse_value(lowercase__			,							cond.column			,							cond.cmp_value      )

										if _is_string(lowercase__      ) and _is_string(lowercase__      ):
															A			=					_normalize_for_match(lowercase__      )
															A			=					_normalize_for_match(lowercase__      )

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

										if not _compare(cond.operator			,							lowercase__			,							lowercase__      ):
															return False
					return True
def    __SCREAMING_SNAKE_CASE						(						lowercase__			,							lowercase__			,							lowercase__      ):
					"""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(lowercase__      )      )

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

					if aggregation_op == _Aggregation.SUM:
										return float(sum(lowercase__      )      )
					elif aggregation_op == _Aggregation.AVERAGE:
										return sum(lowercase__      ) / len(lowercase__      )
					else:
										raise ValueError(F"""Unknown aggregation: {aggregation_op}"""      )
def    __SCREAMING_SNAKE_CASE						(						lowercase__			,							lowercase__      ):
					"""simple docstring"""
					A			=					sql_query["agg"]
					if aggregation_op_index >= 3:
										A			=					_Aggregation(lowercase__      )
					else:
										A			=					_Aggregation.NONE

					A			=					sql_query["sel"]
					A			=					[
					    _Condition(lowercase__			,							_Operator(lowercase__      )			,							lowercase__      )
					    for column, operator, cmp_value in zip(
					        sql_query["conds"]["column_index"]			,							sql_query["conds"]["operator_index"]			,							sql_query["conds"]["condition"]      )
					]

					A			=					[]
					for row in range(len(table["rows"]      )      ):
										if _respect_conditions(lowercase__			,							table["rows"][row]			,							lowercase__      ):
															indices.append((row, target_column)      )

					if not indices:
										return [], aggregation_op

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

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

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

					return indices, aggregation_op
def    __SCREAMING_SNAKE_CASE						(						lowercase__			,							lowercase__			,							lowercase__      ):
					"""simple docstring"""
					if float_answer is not None:
										return [str(lowercase__      )]
					return [str(table["real_rows"][r][c]      ) for r, c in answer_coordinates]
def    __SCREAMING_SNAKE_CASE						(						lowercase__			,							lowercase__      ):
					"""simple docstring"""
					A			,    A			=					_get_answer_coordinates(lowercase__			,							lowercase__      )
					A			=					_get_float_answer(lowercase__			,							lowercase__			,							lowercase__      )
					A			=					_get_answer_text(lowercase__			,							lowercase__			,							lowercase__      )
					# keep the original data the same with TaPas
					if len(lowercase__      ) == 0:
										A			=					[EMPTY_ANSWER]
					return answer_text





