


'''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__	:      Tuple				=						"""none"""
A__	:      int				=						"""none"""



def     UpperCAmelCase__      (			UpperCAmelCase_					:       str   ,					UpperCAmelCase_					:       int							)  ->	Dict:
     __lowerCamelCase     :			Tuple              =	value.split(UpperCAmelCase_							)
     return len(UpperCAmelCase_							) > 1 and any((len(UpperCAmelCase_							) == 3 for x in split)							)



def     UpperCAmelCase__      (			UpperCAmelCase_					:       Optional[Any]							)  ->	List[str]:
     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'							)
     __lowerCamelCase     :			Tuple              =	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_					:       Union[str, Any]							)  ->	Dict:
     if answer is None:
          return None
     try:
          __lowerCamelCase     :			Tuple              =	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						):





    """simple docstring"""






    lowerCamelCase						:      Union[str, Any]							  =    0
    lowerCamelCase						:      Optional[Any]							  =    1
    lowerCamelCase						:      Optional[Any]							  =    2
    lowerCamelCase						:      Any							  =    3
    lowerCamelCase						:      Dict							  =    4
    lowerCamelCase						:      int							  =    5







class      UpperCAmelCase_						(enum.Enum						):





    """simple docstring"""






    lowerCamelCase						:      Optional[int]							  =    0
    lowerCamelCase						:      str							  =    1
    lowerCamelCase						:      List[str]							  =    2







@dataclasses.dataclass
class      UpperCAmelCase_						:





    """simple docstring"""






    lowerCamelCase						:      Text
    lowerCamelCase						:      _Operator
    lowerCamelCase						:      Any







A__	:      Optional[Any]				=						re.compile(R"""\w+|[^\w\s]+""", re.UNICODE | re.MULTILINE | re.DOTALL)



def     UpperCAmelCase__      (			UpperCAmelCase_					:       List[str]							)  ->	Any:
     return list(_TOKENIZER.findall(x.lower()							)							)



def     UpperCAmelCase__      (			UpperCAmelCase_					:       List[str]   ,					UpperCAmelCase_					:       int   ,					UpperCAmelCase_					:       Tuple							)  ->	Union[str, Any]:
     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[str]   ,					UpperCAmelCase_					:       Optional[int]   ,					UpperCAmelCase_					:       Dict							)  ->	Optional[int]:
     __lowerCamelCase     :			Optional[int]              =	table['types']
     return _TYPE_CONVERTER[types[column]](UpperCAmelCase_							)



def     UpperCAmelCase__      (			UpperCAmelCase_					:       Optional[int]							)  ->	Optional[int]:
     return isinstance(UpperCAmelCase_   ,					UpperCAmelCase_							)



def     UpperCAmelCase__      (			UpperCAmelCase_					:       List[str]   ,					UpperCAmelCase_					:       Tuple   ,					UpperCAmelCase_					:       Optional[int]							)  ->	List[str]:
     for cond in conditions:
          __lowerCamelCase     :			str              =	row[cond.column]

          __lowerCamelCase     :			Dict              =	_parse_value(UpperCAmelCase_   ,					cond.column   ,					cond.cmp_value							)

          if _is_string(UpperCAmelCase_							) and _is_string(UpperCAmelCase_							):
               __lowerCamelCase     :			Optional[int]              =	_normalize_for_match(UpperCAmelCase_							)
               __lowerCamelCase     :			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_					:       int   ,					UpperCAmelCase_					:       Dict   ,					UpperCAmelCase_					:       List[Any]							)  ->	Tuple:
     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.
     __lowerCamelCase     :			Dict              =	[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[int]   ,					UpperCAmelCase_					:       List[str]							)  ->	Union[str, Any]:
     __lowerCamelCase     :			Any              =	sql_query['agg']
     if aggregation_op_index >= 3:
          __lowerCamelCase     :			Optional[Any]              =	_Aggregation(UpperCAmelCase_							)
     else:
          __lowerCamelCase     :			Optional[Any]              =	_Aggregation.NONE

     __lowerCamelCase     :			Dict              =	sql_query['sel']
     __lowerCamelCase     :			Optional[Any]              =	[
         _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']							)
     ]

     __lowerCamelCase     :			Optional[int]              =	[]
     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):
          __lowerCamelCase     :			int              =	{2: min, 1: max}
          __lowerCamelCase     :			str              =	[(table['rows'][i][j], index) for index, (i, j) in enumerate(UpperCAmelCase_							)]
          __lowerCamelCase     :			str              =	functools.reduce(operators[sql_query['agg']]   ,					UpperCAmelCase_							)

          __lowerCamelCase     :			Any              =	[indices[reduced[1]]]
          return ret, _Aggregation.NONE

     return indices, aggregation_op



def     UpperCAmelCase__      (			UpperCAmelCase_					:       Tuple   ,					UpperCAmelCase_					:       Any   ,					UpperCAmelCase_					:       str							)  ->	List[str]:
     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_					:       Union[str, Any]   ,					UpperCAmelCase_					:       List[str]							)  ->	List:
     __lowerCamelCase       , __lowerCamelCase     :			List[str]              =	_get_answer_coordinates(UpperCAmelCase_   ,					UpperCAmelCase_							)
     __lowerCamelCase     :			Tuple              =	_get_float_answer(UpperCAmelCase_   ,					UpperCAmelCase_   ,					UpperCAmelCase_							)
     __lowerCamelCase     :			List[Any]              =	_get_answer_text(UpperCAmelCase_   ,					UpperCAmelCase_   ,					UpperCAmelCase_							)
     # keep the original data the same with TaPas
     if len(UpperCAmelCase_							) == 0:
          __lowerCamelCase     :			Union[str, Any]              =	[EMPTY_ANSWER]
     return answer_text










'''simple docstring'''



from typing import TYPE_CHECKING

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


A__	:      Optional[Any]				=						{
    """configuration_xlm_prophetnet""": ["""XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMProphetNetConfig"""],
}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__	:      List[Any]				=						["""XLMProphetNetTokenizer"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__	:      Optional[Any]				=						[
          """XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """XLMProphetNetDecoder""",
          """XLMProphetNetEncoder""",
          """XLMProphetNetForCausalLM""",
          """XLMProphetNetForConditionalGeneration""",
          """XLMProphetNetModel""",
          """XLMProphetNetPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_xlm_prophetnet import (
                XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                XLMProphetNetDecoder,
                XLMProphetNetEncoder,
                XLMProphetNetForCausalLM,
                XLMProphetNetForConditionalGeneration,
                XLMProphetNetModel,
                XLMProphetNetPreTrainedModel,
            )

else:
      import sys

      A__	:      List[str]				=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






