



import argparse
from collections import defaultdict



def    snake_case_				(    _SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   ):
	__lowercase		       =			F"""{file}_{class_name}_{test_name}"""
	done_test[_id] += 1

	with open(_SCREAMING_SNAKE_CASE  ,	"r"   ) as f:
		__lowercase		       =			f.readlines()

	__lowercase		       =			F"""class {class_name}("""
	__lowercase		       =			F"""{4 * ' '}def {test_name}("""
	__lowercase		       =			F"""{8 * ' '}{correct_line.split()[0]}"""
	__lowercase		       =			F"""{1_6 * ' '}{correct_line.split()[0]}"""
	__lowercase		       =			False
	__lowercase		       =			False
	__lowercase		       =			False
	__lowercase		       =			False
	__lowercase		       =			0
	__lowercase		       =			0

	__lowercase		       =			[]
	for line in lines:
		if line.startswith(_SCREAMING_SNAKE_CASE   ):
			__lowercase		       =			True
		elif in_class and line.startswith(_SCREAMING_SNAKE_CASE   ):
			__lowercase		       =			True
		elif in_class and in_func and (line.startswith(_SCREAMING_SNAKE_CASE   ) or line.startswith(_SCREAMING_SNAKE_CASE   )):
			__lowercase		       =			len(line.split(correct_line.split()[0]   )[0]   )
			count += 1

			if count == done_test[_id]:
				__lowercase		       =			True

		if in_class and in_func and in_line:
			if ")" not in line:
				continue
			else:
				__lowercase		       =			True

		if in_class and in_func and in_line and insert_line:
			new_lines.append(F"""{spaces * ' '}{correct_line}"""   )
			__lowercase		       =			__lowercase		       =			__lowercase		       =			__lowercase		       =			False
		else:
			new_lines.append(_SCREAMING_SNAKE_CASE   )

	with open(_SCREAMING_SNAKE_CASE  ,	"w"   ) as f:
		for line in new_lines:
			f.write(_SCREAMING_SNAKE_CASE   )



def    snake_case_				(    _SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE=None   ):
	if fail is not None:
		with open(_SCREAMING_SNAKE_CASE  ,	"r"   ) as f:
			__lowercase		       =			{l.strip() for l in f.readlines()}
	else:
		__lowercase		       =			None

	with open(_SCREAMING_SNAKE_CASE  ,	"r"   ) as f:
		__lowercase		       =			f.readlines()

	__lowercase		       =			defaultdict(_SCREAMING_SNAKE_CASE   )
	for line in correct_lines:
		__lowercase       ,    __lowercase       ,    __lowercase       ,    __lowercase		       =			line.split(";"   )
		if test_failures is None or "::".join([file, class_name, test_name]   ) in test_failures:
			overwrite_file(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   )


if __name__ == "__main__":
	snake_case__					:     List[Any]    		=   argparse.ArgumentParser()
	parser.add_argument("""--correct_filename""", help="""filename of tests with expected result""")
	parser.add_argument("""--fail_filename""", help="""filename of test failures""", type=str, default=None)
	snake_case__					:     Optional[int]    		=   parser.parse_args()

	main(args.correct_filename, args.fail_filename)








# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool

class   _A   ( _lowercase	):


						'''simple docstring'''





						_snake_case			:     Dict      							=      """openai/whisper-base"""
						_snake_case			:     Union[str, Any]      							=      (
						    """This is a tool that transcribes an audio into text. It takes an input named `audio` and returns the """
						    """transcribed text."""
						)
						_snake_case			:     Any      							=      """transcriber"""
						_snake_case			:     Any      							=      WhisperProcessor
						_snake_case			:     Optional[int]      							=      WhisperForConditionalGeneration

						_snake_case			:     str      							=      ["""audio"""]
						_snake_case			:     Optional[int]      							=      ["""text"""]



						def     _snake_case	(	self	:							List[str]							,      lowerCamelCase	:							Optional[int]	):






							'''simple docstring'''



							return self.pre_processor(lowerCamelCase							,      return_tensors="pt"	).input_features



						def     _snake_case	(	self	:							str							,      lowerCamelCase	:							List[Any]	):






							'''simple docstring'''



							return self.model.generate(inputs=lowerCamelCase	)



						def     _snake_case	(	self	:							List[str]							,      lowerCamelCase	:							Optional[Any]	):






							'''simple docstring'''



							return self.pre_processor.batch_decode(lowerCamelCase							,      skip_special_tokens=lowerCamelCase	)[0]



