code: 
  
  
  '''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
  
  
  
  
  
  
  
style_context: 
  
  
  '''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__)
  
  
  
  
  
  
  