'''simple docstring'''




import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate


@dataclass(frozen=_snake_case			)
class       UpperCAmelCase__  (       _snake_case			):






   """simple docstring"""
   A							:       str     =    field(default='''audio-classification'''					,     metadata={'''include_in_asdict_even_if_is_default''': True}			)
   A							:       Tuple     =    Features({'''audio''': Audio()}			)
   A							:       Optional[Any]     =    Features({'''labels''': ClassLabel}			)
   A							:       Optional[int]     =    '''audio'''
   A							:       Any     =    '''labels'''
   def 		_lowerCamelCase (self       ,				_a				)    ->     int:
        if self.label_column not in features:
             raise ValueError(f'''Column {self.label_column} is not present in features.'''				)
        if not isinstance(features[self.label_column]       ,				UpperCAmelCase__				):
             raise ValueError(f'''Column {self.label_column} is not a ClassLabel.'''				)
        lowercase_					:       Any     				=					copy.deepcopy(self				)
        lowercase_					:       List[Any]     				=					self.label_schema.copy()
        lowercase_					:       Any     				=					features[self.label_column]
        lowercase_					:       str     				=					label_schema
        return task_template





   @property
   def 		_lowerCamelCase (self				)    ->     Dict[str, str]:
        return {
            self.audio_column: "audio",
            self.label_column: "labels",
        }





'''simple docstring'''




from __future__ import annotations

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_							):

     # preprocessing the first row
     for i in range(1  ,       len(matrix[0]							)							):
          matrix[0][i] += matrix[0][i - 1]

     # preprocessing the first column
     for i in range(1  ,       len(SCREAMING_SNAKE_CASE_							)							):
          matrix[i][0] += matrix[i - 1][0]

     # updating the path cost for current position
     for i in range(1  ,       len(SCREAMING_SNAKE_CASE_							)							):
          for j in range(1  ,       len(matrix[0]							)							):
               matrix[i][j] += min(matrix[i - 1][j]  ,       matrix[i][j - 1]							)

     return matrix[-1][-1]


if __name__ == "__main__":
 import doctest

 doctest.testmod()




