






'''simple docstring'''

from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def     __lowercase  ()   ->     str:


					"""simple docstring"""
					__lowerCamelCase						:       Any				   =				HfArgumentParser(_lowercase     )
					__lowerCamelCase						:       List[str]				   =				parser.parse_args_into_dataclasses()[0]
					__lowerCamelCase						:       Dict				   =				TensorFlowBenchmark(args=_lowercase     )
					try:
										__lowerCamelCase						:       List[str]				   =				parser.parse_args_into_dataclasses()[0]
					except ValueError as e:
										__lowerCamelCase						:       Tuple				   =				"""Arg --no_{0} is no longer used, please use --no-{0} instead."""
										__lowerCamelCase						:       List[Any]				   =				""" """.join(str(_lowercase     ).split(""" """     )[:-1]     )
										__lowerCamelCase						:       Tuple				   =				""""""
										__lowerCamelCase						:       List[str]				   =				eval(str(_lowercase     ).split(""" """     )[-1]     )
										__lowerCamelCase						:       Tuple				   =				[]
										for arg in depreciated_args:
															# arg[2:] removes '--'
															if arg[2:] in TensorFlowBenchmark.deprecated_args:
																				# arg[5:] removes '--no_'
																				full_error_msg += arg_error_msg.format(arg[5:]     )
															else:
																				wrong_args.append(_lowercase     )
										if len(_lowercase     ) > 0:
															__lowerCamelCase						:       Tuple				   =				full_error_msg + begin_error_msg + str(_lowercase     )
										raise ValueError(_lowercase     )
					benchmark.run()


if __name__ == "__main__":
			main()











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




       def 					a_					(					self      : Any	,    A__      : Any					):


            """simple docstring"""







            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]	,    A__					):
                 raise ValueError(f"Column {self.audio_column} is not an Audio type."					)
            __lowerCamelCase						:       Dict				   =				copy.deepcopy(self					)
            __lowerCamelCase						:       List[Any]				   =				self.input_schema.copy()
            __lowerCamelCase						:       Optional[int]				   =				features[self.audio_column]
            __lowerCamelCase						:       Any				   =				input_schema
            return task_template




       @property
       def 					a_					(					self      : Any					):


            """simple docstring"""







            return {self.audio_column: "audio", self.transcription_column: "transcription"}



