


import string
from math import logaa



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ )-> int:
				lowerCAmelCase_ :      int    				=				document.translate(
				    str.maketrans('''''' ,   '''''' ,   string.punctuation ) ).replace('''\n''' ,   '''''' )
				lowerCAmelCase_ :      Optional[int]    				=				document_without_punctuation.split(''' ''' )  # word tokenization
				return len([word for word in tokenize_document if word.lower() == term.lower()] )



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ )-> tuple[int, int]:
				lowerCAmelCase_ :      Optional[int]    				=				corpus.lower().translate(
				    str.maketrans('''''' ,   '''''' ,   string.punctuation ) )  # strip all punctuation and replace it with ''
				lowerCAmelCase_ :      Optional[Any]    				=				corpus_without_punctuation.split('''\n''' )
				lowerCAmelCase_ :      str    				=				term.lower()
				return (len([doc for doc in docs if term in doc] ), len(__UpperCamelCase ))



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_=False )-> float:
				if smoothing:
								if n == 0:
												raise ValueError('''log10(0) is undefined.''' )
								return round(1 + logaa(n / (1 + df) ) ,   3 )

				if df == 0:
								raise ZeroDivisionError('''df must be > 0''' )
				elif n == 0:
								raise ValueError('''log10(0) is undefined.''' )
				return round(logaa(n / df ) ,   3 )




def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ )-> float:
				return round(tf * idf ,   3 )










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

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







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







						'''simple docstring'''




						SCREAMING_SNAKE_CASE__      :  str					=							field(default="""automatic-speech-recognition""",						metadata={"""include_in_asdict_even_if_is_default""": True}							)
						SCREAMING_SNAKE_CASE__      :  ClassVar[Features]					=							Features({"""audio""": Audio()}							)
						SCREAMING_SNAKE_CASE__      :  ClassVar[Features]					=							Features({"""transcription""": Value("""string"""							)}							)
						SCREAMING_SNAKE_CASE__      :  str					=							"audio"
						SCREAMING_SNAKE_CASE__      :  str					=							"transcription"




						def 						lowercase_ (				self   ,						__lowercase							)					->    int:
										if self.audio_column not in features:
														raise ValueError(f"""Column {self.audio_column} is not present in features."""							)
										if not isinstance(features[self.audio_column]   ,						__lowercase							):
														raise ValueError(f"""Column {self.audio_column} is not an Audio type."""							)
										lowerCAmelCase_ :      List[str]    				=				copy.deepcopy(self							)
										lowerCAmelCase_ :      Optional[Any]    				=				self.input_schema.copy()
										lowerCAmelCase_ :      Optional[Any]    				=				features[self.audio_column]
										lowerCAmelCase_ :      List[str]    				=				input_schema
										return task_template




						@property
						def 						lowercase_ (				self							)					->    Dict[str, str]:
										return {self.audio_column: "audio", self.transcription_column: "transcription"}