



"""simple docstring"""

from __future__ import annotations

from collections import Counter
from random import random







class    __lowercase     :







						"""simple docstring"""







						def __init__(self       ):
											snake_case_					:		Tuple 					=					{}







						def 						__UpperCamelCase							(self   ,		lowercase__       ):
											snake_case_					:		Optional[int] 					=					{}







						def 						__UpperCamelCase							(self   ,		lowercase__   ,		lowercase__   ,		lowercase__       ):
											if nodea not in self.connections:
																self.add_node(lowercase__       )
											if nodea not in self.connections:
																self.add_node(lowercase__       )
											snake_case_					:		Optional[Any] 					=					probability







						def 						__UpperCamelCase							(self       ):
											return list(self.connections       )







						def 						__UpperCamelCase							(self   ,		lowercase__       ):
											snake_case_					:		int 					=					0
											snake_case_					:		List[str] 					=					random()

											for dest in self.connections[node]:
																current_probability += self.connections[node][dest]
																if current_probability > random_value:
																					return dest
											return ""







def 							SCREAMING_SNAKE_CASE__      (		SCREAMING_SNAKE_CASE__ :  str				,    SCREAMING_SNAKE_CASE__ :  list[tuple[str, str, float]]				,    SCREAMING_SNAKE_CASE__ :  int			):



					"""simple docstring"""





					snake_case_					:		Union[str, Any] 					=					MarkovChainGraphUndirectedUnweighted()

					for nodea, nodea, probability in transitions:
										graph.add_transition_probability(SCREAMING_SNAKE_CASE__				,    SCREAMING_SNAKE_CASE__				,    SCREAMING_SNAKE_CASE__			)

					snake_case_					:		Any 					=					Counter(graph.get_nodes()			)
					snake_case_					:		List[str] 					=					start

					for _ in range(SCREAMING_SNAKE_CASE__			):
										snake_case_					:		List[Any] 					=					graph.transition(SCREAMING_SNAKE_CASE__			)
										visited[node] += 1

					return visited


if __name__ == "__main__":
				import doctest

				doctest.testmod()









"""simple docstring"""

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    __lowercase     (					_UpperCAmelCase):







						"""simple docstring"""







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







						def 						__UpperCamelCase							(self   ,		lowercase__       ):
											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.'       )
											snake_case_					:		Optional[int] 					=					copy.deepcopy(self       )
											snake_case_					:		Tuple 					=					self.input_schema.copy()
											snake_case_					:		List[str] 					=					features[self.audio_column]
											snake_case_					:		Any 					=					input_schema
											return task_template







						@property
						def 						__UpperCamelCase							(self       ):
											return {self.audio_column: "audio", self.transcription_column: "transcription"}




