



"""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


_UpperCamelCase:					Optional[int]     				=	'none'
_UpperCamelCase:					List[Any]     				=	'none'


def 	lowercase__  (      _UpperCAmelCase						,   _UpperCAmelCase					)  ->      Dict:






      '''simple docstring'''


      lowercase	:   Dict											= value.split(_UpperCAmelCase					)
      return len(_UpperCAmelCase					) > 1 and any((len(_UpperCAmelCase					) == 3 for x in split)					)


def 	lowercase__  (      _UpperCAmelCase					)  ->      List[str]:






      '''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	:   int											= 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 	lowercase__  (      _UpperCAmelCase					)  ->      Optional[int]:






      '''simple docstring'''


      if answer is None:
            return None
      try:
            lowercase	:   Optional[int]											= convert_to_float(_UpperCAmelCase					)
            if isinstance(_UpperCAmelCase						,   _UpperCAmelCase					) and math.isnan(_UpperCAmelCase					):
                  return None
            return value
      except ValueError:
            return answer.lower()


_UpperCamelCase:					Optional[Any]     				=	{
    'text': lambda x: x,
    'real': convert_to_float,
}


class 	a__		(    enum.Enum  ):
   _lowerCamelCase       				=					0
   _lowerCamelCase       				=					1
   _lowerCamelCase       				=					2
   _lowerCamelCase       				=					3
   _lowerCamelCase       				=					4
   _lowerCamelCase       				=					5




class 	a__		(    enum.Enum  ):
   _lowerCamelCase       				=					0
   _lowerCamelCase       				=					1
   _lowerCamelCase       				=					2




@dataclasses.dataclass
class 	a__		:
   _lowerCamelCase       				=					42
   _lowerCamelCase       				=					42
   _lowerCamelCase       				=					42




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


def 	lowercase__  (      _UpperCAmelCase					)  ->      int:






      '''simple docstring'''


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


def 	lowercase__  (      _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 	lowercase__  (      _UpperCAmelCase						,   _UpperCAmelCase						,   _UpperCAmelCase					)  ->      Union[str, Any]:






      '''simple docstring'''


      lowercase	:   Union[str, Any]											= table['types']
      return _TYPE_CONVERTER[types[column]](_UpperCAmelCase					)


def 	lowercase__  (      _UpperCAmelCase					)  ->      int:






      '''simple docstring'''


      return isinstance(_UpperCAmelCase						,   _UpperCAmelCase					)


def 	lowercase__  (      _UpperCAmelCase						,   _UpperCAmelCase						,   _UpperCAmelCase					)  ->      Dict:






      '''simple docstring'''


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

            lowercase	:   List[str]											= _parse_value(_UpperCAmelCase						,   cond.column						,   cond.cmp_value					)

            if _is_string(_UpperCAmelCase					) and _is_string(_UpperCAmelCase					):
                  lowercase	:   str											= _normalize_for_match(_UpperCAmelCase					)
                  lowercase	:   Optional[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 	lowercase__  (      _UpperCAmelCase						,   _UpperCAmelCase						,   _UpperCAmelCase					)  ->      List[str]:






      '''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	:   int											= [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 	lowercase__  (      _UpperCAmelCase						,   _UpperCAmelCase					)  ->      str:






      '''simple docstring'''


      lowercase	:   Dict											= sql_query['agg']
      if aggregation_op_index >= 3:
            lowercase	:   List[Any]											= _Aggregation(_UpperCAmelCase					)
      else:
            lowercase	:   Optional[Any]											= _Aggregation.NONE

      lowercase	:   List[Any]											= sql_query['sel']
      lowercase	:   List[str]											= [
          _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	:   str											= {2: min, 1: max}
            lowercase	:   Dict											= [(table['rows'][i][j], index) for index, (i, j) in enumerate(_UpperCAmelCase					)]
            lowercase	:   str											= functools.reduce(operators[sql_query['agg']]						,   _UpperCAmelCase					)

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

      return indices, aggregation_op


def 	lowercase__  (      _UpperCAmelCase						,   _UpperCAmelCase						,   _UpperCAmelCase					)  ->      Dict:






      '''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 	lowercase__  (      _UpperCAmelCase						,   _UpperCAmelCase					)  ->      List:






      '''simple docstring'''


      lowercase						,     lowercase	:   Tuple											= _get_answer_coordinates(_UpperCAmelCase						,   _UpperCAmelCase					)
      lowercase	:   Optional[int]											= _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





"""simple docstring"""




from typing import TYPE_CHECKING

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


_UpperCamelCase:					Optional[Any]     				=	{
    'configuration_codegen': ['CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CodeGenConfig', 'CodeGenOnnxConfig'],
    'tokenization_codegen': ['CodeGenTokenizer'],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase:					Union[str, Any]     				=	['CodeGenTokenizerFast']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase:					str     				=	[
         'CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST',
         'CodeGenForCausalLM',
         'CodeGenModel',
         'CodeGenPreTrainedModel',
     ]

if TYPE_CHECKING:
     from .configuration_codegen import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, CodeGenConfig, CodeGenOnnxConfig
     from .tokenization_codegen import CodeGenTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_codegen_fast import CodeGenTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_codegen import (
              CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
              CodeGenForCausalLM,
              CodeGenModel,
              CodeGenPreTrainedModel,
          )

else:
     import sys

     _UpperCamelCase:					int     				=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
