
"""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      :	Optional[int]       		=	"""none"""
_A      :	List[str]       		=	"""none"""
def   __magic_name__     (				__snake_case    :	Dict					,			__snake_case    :	Tuple  )			->    str:
       lowercase   :    Tuple			=							value.split(__snake_case  )
       return len(__snake_case  ) > 1 and any((len(__snake_case  ) == 3 for x in split)  )
def   __magic_name__     (				__snake_case    :	Optional[int]  )			->    List[Any]:
       if isinstance(__snake_case					,			__snake_case  ):
              return value
       if isinstance(__snake_case					,			__snake_case  ):
              return float(__snake_case  )
       if not isinstance(__snake_case					,			__snake_case  ):
              raise ValueError("Argument value is not a string. Can't parse it as float"  )
       lowercase   :    List[str]			=							value

       try:
              # Example: 1,000.7
              if "." in sanitized and "," in sanitized:
                     return float(sanitized.replace(","					,			""  )  )
              # 1,000
              if "," in sanitized and _split_thousands(","					,			__snake_case  ):
                     return float(sanitized.replace(","					,			""  )  )
              # 5,5556
              if "," in sanitized and sanitized.count(","  ) == 1 and not _split_thousands(","					,			__snake_case  ):
                     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(__snake_case  )
       except ValueError:
              # Avoid adding the sanitized value in the error message.
              raise ValueError("Unable to convert value to float"  )
def   __magic_name__     (				__snake_case    :	Dict  )			->    Optional[Any]:
       if answer is None:
              return None
       try:
              lowercase   :    Tuple			=							convert_to_float(__snake_case  )
              if isinstance(__snake_case					,			__snake_case  ) and math.isnan(__snake_case  ):
                     return None
              return value
       except ValueError:
              return answer.lower()


_A      :	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


_A      :	Tuple       		=	re.compile(r"""\w+|[^\w\s]+""", re.UNICODE | re.MULTILINE | re.DOTALL)
def   __magic_name__     (				__snake_case    :	Optional[Any]  )			->    Union[str, Any]:
       return list(_TOKENIZER.findall(x.lower()  )  )
def   __magic_name__     (				__snake_case    :	int					,			__snake_case    :	Union[str, Any]					,			__snake_case    :	List[Any]  )			->    Optional[int]:
       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   __magic_name__     (				__snake_case    :	Dict					,			__snake_case    :	Tuple					,			__snake_case    :	Optional[int]  )			->    Any:
       lowercase   :    int			=							table["types"]
       return _TYPE_CONVERTER[types[column]](__snake_case  )
def   __magic_name__     (				__snake_case    :	int  )			->    List[str]:
       return isinstance(__snake_case					,			__snake_case  )
def   __magic_name__     (				__snake_case    :	List[str]					,			__snake_case    :	Tuple					,			__snake_case    :	Any  )			->    Tuple:
       for cond in conditions:
              lowercase   :    List[Any]			=							row[cond.column]

              lowercase   :    Tuple			=							_parse_value(__snake_case					,			cond.column					,			cond.cmp_value  )

              if _is_string(__snake_case  ) and _is_string(__snake_case  ):
                     lowercase   :    Union[str, Any]			=							_normalize_for_match(__snake_case  )
                     lowercase   :    Tuple			=							_normalize_for_match(__snake_case  )

              if not isinstance(__snake_case					,			type(__snake_case  )  ):
                     raise ValueError("Type difference {} != {}".format(type(__snake_case  )					,			type(__snake_case  )  )  )

              if not _compare(cond.operator					,			__snake_case					,			__snake_case  ):
                     return False
       return True
def   __magic_name__     (				__snake_case    :	Optional[Any]					,			__snake_case    :	List[Any]					,			__snake_case    :	Any  )			->    int:
       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(__snake_case  )  )

       # If we have just one answer, if float returns it or try a conversion.
       lowercase   :    Union[str, Any]			=							[table["rows"][i][j] for (i, j) in answer_coordinates]
       if len(__snake_case  ) == 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(__snake_case					,			(int, float)  ) for v in values)  ):
              return None

       if aggregation_op == _Aggregation.SUM:
              return float(sum(__snake_case  )  )
       elif aggregation_op == _Aggregation.AVERAGE:
              return sum(__snake_case  ) / len(__snake_case  )
       else:
              raise ValueError(f"""Unknown aggregation: {aggregation_op}"""  )
def   __magic_name__     (				__snake_case    :	Union[str, Any]					,			__snake_case    :	int  )			->    Dict:
       lowercase   :    Union[str, Any]			=							sql_query["agg"]
       if aggregation_op_index >= 3:
              lowercase   :    List[Any]			=							_Aggregation(__snake_case  )
       else:
              lowercase   :    Any			=							_Aggregation.NONE

       lowercase   :    List[str]			=							sql_query["sel"]
       lowercase   :    List[Any]			=							[
           _Condition(__snake_case					,			_Operator(__snake_case  )					,			__snake_case  )
           for column, operator, cmp_value in zip(
               sql_query["conds"]["column_index"]					,			sql_query["conds"]["operator_index"]					,			sql_query["conds"]["condition"]  )
       ]

       lowercase   :    List[Any]			=							[]
       for row in range(len(table["rows"]  )  ):
              if _respect_conditions(__snake_case					,			table["rows"][row]					,			__snake_case  ):
                     indices.append((row, target_column)  )

       if not indices:
              return [], aggregation_op

       if len(__snake_case  ) == 1:
              return indices, aggregation_op

       # Parsing of MIN/MAX.
       if aggregation_op_index in (1, 2):
              lowercase   :    Dict			=							{2: min, 1: max}
              lowercase   :    Tuple			=							[(table["rows"][i][j], index) for index, (i, j) in enumerate(__snake_case  )]
              lowercase   :    List[str]			=							functools.reduce(operators[sql_query["agg"]]					,			__snake_case  )

              lowercase   :    Union[str, Any]			=							[indices[reduced[1]]]
              return ret, _Aggregation.NONE

       return indices, aggregation_op
def   __magic_name__     (				__snake_case    :	Optional[int]					,			__snake_case    :	Optional[int]					,			__snake_case    :	int  )			->    Union[str, Any]:
       if float_answer is not None:
              return [str(__snake_case  )]
       return [str(table["real_rows"][r][c]  ) for r, c in answer_coordinates]
def   __magic_name__     (				__snake_case    :	List[str]					,			__snake_case    :	Optional[int]  )			->    List:
       lowercase   :    int			=							_get_answer_coordinates(__snake_case					,			__snake_case  )
       lowercase   :    str			=							_get_float_answer(__snake_case					,			__snake_case					,			__snake_case  )
       lowercase   :    Optional[int]			=							_get_answer_text(__snake_case					,			__snake_case					,			__snake_case  )
       # keep the original data the same with TaPas
       if len(__snake_case  ) == 0:
              lowercase   :    int			=							[EMPTY_ANSWER]
       return answer_text




"""simple docstring"""




from ...configuration_utils import PretrainedConfig
from ...utils import logging


_A      :	str       		=	logging.get_logger(__name__)

_A      :	Optional[int]       		=	{
    """ZinengTang/tvlt-base""": """https://huggingface.co/ZinengTang/tvlt-base/blob/main/config.json""",
}

class 		a__						(				a_						):
   __lowerCAmelCase						=    """tvlt"""
   def __init__(      self     ,   _a=224     ,   _a=2_048     ,   _a=128     ,   _a=[16, 16]     ,   _a=[16, 16]     ,   _a=3     ,   _a=1     ,   _a=8     ,   _a=768     ,   _a=12     ,   _a=12     ,   _a=3_072     ,   _a="gelu"     ,   _a=0.0     ,   _a=0.0     ,   _a=0.0_2     ,   _a=1E-6     ,   _a=True     ,   _a=False     ,   _a=16     ,   _a=512     ,   _a=8     ,   _a=2_048     ,   _a=0.7_5     ,   _a=0.1_5     ,   _a="frame-level"     ,   _a=True     ,   _a=True     ,   _a="classification"     ,   **_a     ,   ):
          super().__init__(**_a    )

          if audio_mask_type not in ("frame-level", "patch_level"):
                 raise ValueError(
                     "audio_mask_type must be one of two acceptable strategies - {'frame_level', 'patch-level') "
                     f"""got {audio_mask_type}"""    )

          lowercase   :    Union[str, Any]			=							image_size
          lowercase   :    Dict			=							spectrogram_length
          lowercase   :    Union[str, Any]			=							frequency_length
          lowercase   :    Union[str, Any]			=							image_patch_size
          lowercase   :    Any			=							audio_patch_size
          lowercase   :    int			=							num_image_channels
          lowercase   :    Union[str, Any]			=							num_audio_channels
          lowercase   :    Any			=							num_frames

          lowercase   :    List[str]			=							hidden_size
          lowercase   :    List[str]			=							num_hidden_layers
          lowercase   :    List[Any]			=							num_attention_heads
          lowercase   :    int			=							intermediate_size
          lowercase   :    Tuple			=							hidden_act
          lowercase   :    int			=							hidden_dropout_prob
          lowercase   :    Dict			=							attention_probs_dropout_prob
          lowercase   :    List[Any]			=							initializer_range
          lowercase   :    Union[str, Any]			=							layer_norm_eps
          lowercase   :    Dict			=							qkv_bias
          lowercase   :    List[Any]			=							use_mean_pooling

          lowercase   :    List[Any]			=							decoder_num_attention_heads
          lowercase   :    Union[str, Any]			=							decoder_hidden_size
          lowercase   :    Dict			=							decoder_num_hidden_layers
          lowercase   :    Union[str, Any]			=							decoder_intermediate_size
          lowercase   :    List[str]			=							pixel_mask_ratio
          lowercase   :    str			=							audio_mask_ratio
          lowercase   :    Any			=							audio_mask_type

          lowercase   :    Union[str, Any]			=							task_matching
          lowercase   :    Optional[Any]			=							task_mae
          lowercase   :    List[str]			=							loss_type


