




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__						:       Optional[int]							=    """none"""
UpperCAmelCase__						:       Optional[int]							=    """none"""


def 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase							)			->		int:





  """simple docstring"""





  _lowercase: int						     =    value.split(UpperCamelCase							)
  return len(UpperCamelCase							) > 1 and any((len(UpperCamelCase							) == 3 for x in split)							)


def 		_lowerCamelCase				(					UpperCamelCase							)			->		Union[str, Any]:





  """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'							)
  _lowercase: List[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 		_lowerCamelCase				(					UpperCamelCase							)			->		List[Any]:





  """simple docstring"""





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


UpperCAmelCase__						:       Tuple							=    {
    """text""": lambda x: x,
    """real""": convert_to_float,
}

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

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

@dataclasses.dataclass
class      UpperCAmelCase						:
   __SCREAMING_SNAKE_CASE		:							Text
   __SCREAMING_SNAKE_CASE		:							_Operator
   __SCREAMING_SNAKE_CASE		:							Any
UpperCAmelCase__						:       Tuple							=    re.compile(r'\w+|[^\w\s]+', re.UNICODE | re.MULTILINE | re.DOTALL)


def 		_lowerCamelCase				(					UpperCamelCase							)			->		str:





  """simple docstring"""





  return list(_TOKENIZER.findall(x.lower()							)							)


def 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)			->		int:





  """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 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)			->		Optional[int]:





  """simple docstring"""





  _lowercase: Optional[int]						     =    table["types"]
  return _TYPE_CONVERTER[types[column]](UpperCamelCase							)


def 		_lowerCamelCase				(					UpperCamelCase							)			->		int:





  """simple docstring"""





  return isinstance(UpperCamelCase					,     UpperCamelCase							)


def 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)			->		int:





  """simple docstring"""





  for cond in conditions:
    _lowercase: Tuple						     =    row[cond.column]

    _lowercase: List[Any]						     =    _parse_value(UpperCamelCase					,     cond.column					,     cond.cmp_value							)

    if _is_string(UpperCamelCase							) and _is_string(UpperCamelCase							):
      _lowercase: Any						     =    _normalize_for_match(UpperCamelCase							)
      _lowercase: Union[str, Any]						     =    _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 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)			->		Optional[int]:





  """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.
  _lowercase: Tuple						     =    [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 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase							)			->		Optional[int]:





  """simple docstring"""





  _lowercase: Union[str, Any]						     =    sql_query["agg"]
  if aggregation_op_index >= 3:
    _lowercase: Dict						     =    _Aggregation(UpperCamelCase							)
  else:
    _lowercase: Any						     =    _Aggregation.NONE

  _lowercase: Optional[Any]						     =    sql_query["sel"]
  _lowercase: Optional[int]						     =    [
      _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']							)
  ]

  _lowercase: 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):
    _lowercase: Dict						     =    {2: min, 1: max}
    _lowercase: Optional[Any]						     =    [(table["rows"][i][j], index) for index, (i, j) in enumerate(UpperCamelCase							)]
    _lowercase: Optional[Any]						     =    functools.reduce(operators[sql_query['agg']]					,     UpperCamelCase							)

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

  return indices, aggregation_op


def 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)			->		int:





  """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 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase							)			->		str:





  """simple docstring"""





  _lowercase: Union[str, Any]						     =    _get_answer_coordinates(UpperCamelCase					,     UpperCamelCase							)
  _lowercase: Dict						     =    _get_float_answer(UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)
  _lowercase: Union[str, Any]						     =    _get_answer_text(UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)
  # keep the original data the same with TaPas
  if len(UpperCamelCase							) == 0:
    _lowercase: Dict						     =    [EMPTY_ANSWER]
  return answer_text






from typing import TYPE_CHECKING

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


UpperCAmelCase__						:       Union[str, Any]							=    {'configuration_bert_generation': ['BertGenerationConfig']}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase__						:       str							=    ['BertGenerationTokenizer']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase__						:       Tuple							=    [
       'BertGenerationDecoder',
       'BertGenerationEncoder',
       'BertGenerationPreTrainedModel',
       'load_tf_weights_in_bert_generation',
   ]


if TYPE_CHECKING:
   from .configuration_bert_generation import BertGenerationConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_bert_generation import BertGenerationTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_bert_generation import (
          BertGenerationDecoder,
          BertGenerationEncoder,
          BertGenerationPreTrainedModel,
          load_tf_weights_in_bert_generation,
      )

else:
   import sys

   UpperCAmelCase__						:       List[Any]							=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
