
"""simple docstring"""






import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_multi_gpu,
    require_single_gpu,
    test_sync,
)
from accelerate.utils import patch_environment



class  lowercase				(   unittest.TestCase		):






			def 				UpperCAmelCase       (self     :  Dict )					->  int:





				"""simple docstring"""


				lowerCAmelCase				       =     inspect.getfile(accelerate.test_utils )
				lowerCAmelCase				       =     os.path.sep.join(mod_file.split(os.path.sep )[:-1] + ['''scripts''', '''test_sync.py'''] )






			@require_cpu
			def 				UpperCAmelCase       (self     :  List[str] )					->  str:





				"""simple docstring"""


				debug_launcher(test_sync.main			,num_processes=1 )






			@require_cpu
			def 				UpperCAmelCase       (self     :  Optional[Any] )					->  Any:





				"""simple docstring"""


				debug_launcher(test_sync.main )






			@require_single_gpu
			def 				UpperCAmelCase       (self     :  Optional[Any] )					->  Dict:





				"""simple docstring"""


				test_sync.main()






			@require_multi_gpu
			def 				UpperCAmelCase       (self     :  Dict )					->  Optional[Any]:





				"""simple docstring"""


				print(F"""Found {torch.cuda.device_count()} devices.""" )
				lowerCAmelCase				       =     ['''torchrun''', F"""--nproc_per_node={torch.cuda.device_count()}""", self.test_file_path]
				with patch_environment(omp_num_threads=1 ):
					execute_subprocess_async(SCREAMING_SNAKE_CASE_			,env=os.environ.copy() )




"""simple docstring"""






from typing import Optional

from ..utils.logging import get_logger
from .audio_classificiation import AudioClassification
from .automatic_speech_recognition import AutomaticSpeechRecognition
from .base import TaskTemplate
from .image_classification import ImageClassification
from .language_modeling import LanguageModeling
from .question_answering import QuestionAnsweringExtractive
from .summarization import Summarization
from .text_classification import TextClassification


UpperCAmelCase          =							[
    """AutomaticSpeechRecognition""",
    """AudioClassification""",
    """ImageClassification""",
    """LanguageModeling""",
    """QuestionAnsweringExtractive""",
    """Summarization""",
    """TaskTemplate""",
    """TextClassification""",
]

UpperCAmelCase          =							get_logger(__name__)


UpperCAmelCase          =							{
    AutomaticSpeechRecognition.task: AutomaticSpeechRecognition,
    AudioClassification.task: AudioClassification,
    ImageClassification.task: ImageClassification,
    LanguageModeling.task: LanguageModeling,
    QuestionAnsweringExtractive.task: QuestionAnsweringExtractive,
    Summarization.task: Summarization,
    TextClassification.task: TextClassification,
}




def __magic_name__  (							_lowerCamelCase:		dict )				->	Optional[TaskTemplate]:

	'''simple docstring'''




	lowerCAmelCase				       =     task_template_dict.get('''task''' )
	if task_name is None:
		logger.warning(F"""Couldn't find template for task '{task_name}'. Available templates: {list(_lowerCamelCase )}""" )
		return None
	lowerCAmelCase				       =     NAMEaTEMPLATE.get(_lowerCamelCase )
	return template.from_dict(_lowerCamelCase )


