code: 
  
  
  
  
  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							    =	'none'
  _A							    =	'none'
  def 						lowerCAmelCase_       (	__a	,	__a ):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE			: Any	     =value.split(__a )
  							return len(__a ) > 1 and any((len(__a ) == 3 for x in split) )
  def 						lowerCAmelCase_       (	__a ):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							if isinstance(__a	,	__a ):
  														return value
  							if isinstance(__a	,	__a ):
  														return float(__a )
  							if not isinstance(__a	,	__a ):
  														raise ValueError('''Argument value is not a string. Can\'t parse it as float''' )
  							SCREAMING_SNAKE_CASE			: 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(''','''	,	__a ):
  																					return float(sanitized.replace(''','''	,	'''''' ) )
  														# 5,5556
  														if "," in sanitized and sanitized.count(''',''' ) == 1 and not _split_thousands(''','''	,	__a ):
  																					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(__a )
  							except ValueError:
  														# Avoid adding the sanitized value in the error message.
  														raise ValueError('''Unable to convert value to float''' )
  def 						lowerCAmelCase_       (	__a ):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							if answer is None:
  														return None
  							try:
  														SCREAMING_SNAKE_CASE			: Union[str, Any]	     =convert_to_float(__a )
  														if isinstance(__a	,	__a ) and math.isnan(__a ):
  																					return None
  														return value
  							except ValueError:
  														return answer.lower()
  
  
  _A							    =	{
      'text': lambda x: x,
      'real': convert_to_float,
  }
  
  
  class 							_lowerCAmelCase		(     enum.Enum	):
  				lowerCamelCase__									=    0
  				lowerCamelCase__									=    1
  				lowerCamelCase__									=    2
  				lowerCamelCase__									=    3
  				lowerCamelCase__									=    4
  				lowerCamelCase__									=    5
  
  
  
  
  
  
  
  class 							_lowerCAmelCase		(     enum.Enum	):
  				lowerCamelCase__									=    0
  				lowerCamelCase__									=    1
  				lowerCamelCase__									=    2
  
  
  
  
  
  
  
  @dataclasses.dataclass
  class 							_lowerCAmelCase		:
  				lowerCamelCase__									=    42
  				lowerCamelCase__									=    42
  				lowerCamelCase__									=    42
  
  
  
  
  
  
  
  _A							    =	re.compile(r"""\w+|[^\w\s]+""", re.UNICODE | re.MULTILINE | re.DOTALL)
  def 						lowerCAmelCase_       (	__a ):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							return list(_TOKENIZER.findall(x.lower() ) )
  def 						lowerCAmelCase_       (	__a	,	__a	,	__a ):
  
  
  
  
  
  							"""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_       (	__a	,	__a	,	__a ):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE			: str	     =table['''types''']
  							return _TYPE_CONVERTER[types[column]](__a )
  def 						lowerCAmelCase_       (	__a ):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							return isinstance(__a	,	__a )
  def 						lowerCAmelCase_       (	__a	,	__a	,	__a ):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							for cond in conditions:
  														SCREAMING_SNAKE_CASE			: List[Any]	     =row[cond.column]
  
  														SCREAMING_SNAKE_CASE			: Any	     =_parse_value(__a	,	cond.column	,	cond.cmp_value )
  
  														if _is_string(__a ) and _is_string(__a ):
  																					SCREAMING_SNAKE_CASE			: str	     =_normalize_for_match(__a )
  																					SCREAMING_SNAKE_CASE			: Any	     =_normalize_for_match(__a )
  
  														if not isinstance(__a	,	type(__a ) ):
  																					raise ValueError('''Type difference {} != {}'''.format(type(__a )	,	type(__a ) ) )
  
  														if not _compare(cond.operator	,	__a	,	__a ):
  																					return False
  							return True
  def 						lowerCAmelCase_       (	__a	,	__a	,	__a ):
  
  
  
  
  
  							"""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(__a ) )
  
  							# If we have just one answer, if float returns it or try a conversion.
  							SCREAMING_SNAKE_CASE			: int	     =[table['''rows'''][i][j] for (i, j) in answer_coordinates]
  							if len(__a ) == 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(__a	,	(int, float) ) for v in values) ):
  														return None
  
  							if aggregation_op == _Aggregation.SUM:
  														return float(sum(__a ) )
  							elif aggregation_op == _Aggregation.AVERAGE:
  														return sum(__a ) / len(__a )
  							else:
  														raise ValueError(f'Unknown aggregation: {aggregation_op}' )
  def 						lowerCAmelCase_       (	__a	,	__a ):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE			: List[str]	     =sql_query['''agg''']
  							if aggregation_op_index >= 3:
  														SCREAMING_SNAKE_CASE			: List[str]	     =_Aggregation(__a )
  							else:
  														SCREAMING_SNAKE_CASE			: Dict	     =_Aggregation.NONE
  
  							SCREAMING_SNAKE_CASE			: Optional[int]	     =sql_query['''sel''']
  							SCREAMING_SNAKE_CASE			: Any	     =[
  							    _Condition(__a	,	_Operator(__a )	,	__a )
  							    for column, operator, cmp_value in zip(
  							        sql_query['''conds''']['''column_index''']	,	sql_query['''conds''']['''operator_index''']	,	sql_query['''conds''']['''condition'''] )
  							]
  
  							SCREAMING_SNAKE_CASE			: Any	     =[]
  							for row in range(len(table['''rows'''] ) ):
  														if _respect_conditions(__a	,	table['''rows'''][row]	,	__a ):
  																					indices.append((row, target_column) )
  
  							if not indices:
  														return [], aggregation_op
  
  							if len(__a ) == 1:
  														return indices, aggregation_op
  
  							# Parsing of MIN/MAX.
  							if aggregation_op_index in (1, 2):
  														SCREAMING_SNAKE_CASE			: List[Any]	     ={2: min, 1: max}
  														SCREAMING_SNAKE_CASE			: int	     =[(table['''rows'''][i][j], index) for index, (i, j) in enumerate(__a )]
  														SCREAMING_SNAKE_CASE			: Dict	     =functools.reduce(operators[sql_query['''agg''']]	,	__a )
  
  														SCREAMING_SNAKE_CASE			: Tuple	     =[indices[reduced[1]]]
  														return ret, _Aggregation.NONE
  
  							return indices, aggregation_op
  def 						lowerCAmelCase_       (	__a	,	__a	,	__a ):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							if float_answer is not None:
  														return [str(__a )]
  							return [str(table['''real_rows'''][r][c] ) for r, c in answer_coordinates]
  def 						lowerCAmelCase_       (	__a	,	__a ):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  							SCREAMING_SNAKE_CASE     ,							SCREAMING_SNAKE_CASE			: Any	     =_get_answer_coordinates(__a	,	__a )
  							SCREAMING_SNAKE_CASE			: Dict	     =_get_float_answer(__a	,	__a	,	__a )
  							SCREAMING_SNAKE_CASE			: Tuple	     =_get_answer_text(__a	,	__a	,	__a )
  							# keep the original data the same with TaPas
  							if len(__a ) == 0:
  														SCREAMING_SNAKE_CASE			: str	     =[EMPTY_ANSWER]
  							return answer_text
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_flax_available,
      is_tf_available,
      is_torch_available,
  )
  
  
  _A							    =	{"""configuration_regnet""": ["""REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RegNetConfig"""]}
  
  try:
  							if not is_torch_available():
  														raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  							pass
  else:
  							_A							    =	[
  							    """REGNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
  							    """RegNetForImageClassification""",
  							    """RegNetModel""",
  							    """RegNetPreTrainedModel""",
  							]
  
  try:
  							if not is_tf_available():
  														raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  							pass
  else:
  							_A							    =	[
  							    """TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
  							    """TFRegNetForImageClassification""",
  							    """TFRegNetModel""",
  							    """TFRegNetPreTrainedModel""",
  							]
  
  try:
  							if not is_flax_available():
  														raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  							pass
  else:
  							_A							    =	[
  							    """FlaxRegNetForImageClassification""",
  							    """FlaxRegNetModel""",
  							    """FlaxRegNetPreTrainedModel""",
  							]
  
  
  if TYPE_CHECKING:
  							from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig
  
  							try:
  														if not is_torch_available():
  																					raise OptionalDependencyNotAvailable()
  							except OptionalDependencyNotAvailable:
  														pass
  							else:
  														from .modeling_regnet import (
  														    REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
  														    RegNetForImageClassification,
  														    RegNetModel,
  														    RegNetPreTrainedModel,
  														)
  
  							try:
  														if not is_tf_available():
  																					raise OptionalDependencyNotAvailable()
  							except OptionalDependencyNotAvailable:
  														pass
  							else:
  														from .modeling_tf_regnet import (
  														    TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
  														    TFRegNetForImageClassification,
  														    TFRegNetModel,
  														    TFRegNetPreTrainedModel,
  														)
  
  							try:
  														if not is_flax_available():
  																					raise OptionalDependencyNotAvailable()
  							except OptionalDependencyNotAvailable:
  														pass
  							else:
  														from .modeling_flax_regnet import (
  														    FlaxRegNetForImageClassification,
  														    FlaxRegNetModel,
  														    FlaxRegNetPreTrainedModel,
  														)
  
  
  else:
  							import sys
  
  							_A							    =	_LazyModule(__name__, globals()["""__file__"""], _import_structure)
  
  
  
  
  
  
  