



from ...processing_utils import ProcessorMixin






class    SCREAMING_SNAKE_CASE			(							lowerCamelCase__					):
							__lowerCamelCase	:	Union[str, Any]    =['image_processor', 'feature_extractor']
							__lowerCamelCase	:	Tuple    ='TvltImageProcessor'
							__lowerCamelCase	:	Optional[Any]    ='TvltFeatureExtractor'





							def __init__(   self		:		List[Any]      ,				__lowercase		:		str      ,				__lowercase		:		Optional[int]	):

											'''simple docstring'''
											super().__init__(image_processor=__lowercase      ,				feature_extractor=__lowercase	)

											__a       =		image_processor
											__a       =		feature_extractor





							def __call__(   self		:		Tuple      ,				__lowercase		:		Optional[Any]=None      ,				__lowercase		:		List[str]=None      ,				__lowercase		:		List[str]=None      ,				__lowercase		:		str=None      ,				__lowercase		:		Optional[int]=False      ,				__lowercase		:		Optional[Any]=False      ,				*__lowercase		:		int      ,				**__lowercase		:		Any      ,				):

											'''simple docstring'''

											if images is None and audio is None:
															raise ValueError("""You need to specify either an `images` or `audio` input to process."""	)

											__a       =		None
											if images is not None:
															__a       =		self.image_processor(__lowercase      ,				mask_pixel=__lowercase      ,				*__lowercase      ,				**__lowercase	)
											if images_mixed is not None:
															__a       =		self.image_processor(__lowercase      ,				is_mixed=__lowercase      ,				*__lowercase      ,				**__lowercase	)
											if audio is not None:
															__a       =		self.feature_extractor(
															    __lowercase      ,				*__lowercase      ,				sampling_rate=__lowercase      ,				mask_audio=__lowercase      ,				**__lowercase	)

											__a       =		{}
											if audio is not None:
															output_dict.update(__lowercase	)
											if images is not None:
															output_dict.update(__lowercase	)
											if images_mixed_dict is not None:
															output_dict.update(__lowercase	)
											return output_dict







							@property
							def 						UpperCamelCase_					(   self		:		str	):

											'''simple docstring'''
											__a       =		self.image_processor.model_input_names
											__a       =		self.feature_extractor.model_input_names
											return list(dict.fromkeys(image_processor_input_names + feature_extractor_input_names	)	)





import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict






@dataclass
class    SCREAMING_SNAKE_CASE			(							lowerCamelCase__					):
							__lowerCamelCase	:	List[Any]    =ComputeEnvironment.AMAZON_SAGEMAKER
							__lowerCamelCase	:	Optional[int]    =True
							__lowerCamelCase	:	List[Any]    ='ml.p3.2xlarge'
							__lowerCamelCase	:	Optional[int]    ='accelerate_sagemaker_execution_role'
							__lowerCamelCase	:	Optional[Any]    ='hf-sm'
							__lowerCamelCase	:	Any    ='us-east-1'
							__lowerCamelCase	:	Any    =1
							__lowerCamelCase	:	List[str]    ='accelerate-sagemaker-1'
							__lowerCamelCase	:	Union[str, Any]    ='1.6'
							__lowerCamelCase	:	str    ='4.4'
							__lowerCamelCase	:	List[str]    ='train.py'
							__lowerCamelCase	:	List[Any]    =[
							    '--model_name_or_path',
							    'bert',
							    '--do_train',
							    'False',
							    '--epochs',
							    '3',
							    '--learning_rate',
							    '5e-5',
							    '--max_steps',
							    '50.5',
							]
							__lowerCamelCase	:	Tuple    =[
							    '--model_name_or_path',
							    'bert',
							    '--do_train',
							    '--do_test',
							    'False',
							    '--do_predict',
							    '--epochs',
							    '3',
							    '--learning_rate',
							    '5e-5',
							    '--max_steps',
							    '50.5',
							]






class    SCREAMING_SNAKE_CASE			(							unittest.TestCase					):





							def 						UpperCamelCase_					(   self		:		Union[str, Any]	):

											'''simple docstring'''
											# If no defaults are changed, `to_kwargs` returns an empty dict.
											__a       =		_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args	)
											assert isinstance(converted_args["""model_name_or_path"""]      ,				__lowercase	)
											assert isinstance(converted_args["""do_train"""]      ,				__lowercase	)
											assert isinstance(converted_args["""epochs"""]      ,				__lowercase	)
											assert isinstance(converted_args["""learning_rate"""]      ,				__lowercase	)
											assert isinstance(converted_args["""max_steps"""]      ,				__lowercase	)

											with pytest.raises(__lowercase	):
															_convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args	)
