

"""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 			__UpperCamelCase (   unittest.TestCase						):


		def 					SCREAMING_SNAKE_CASE__   (self :		List[str]):
							A			=					inspect.getfile(accelerate.test_utils)
							A			=					os.path.sep.join(mod_file.split(os.path.sep)[:-1] + ["scripts", "test_sync.py"])


		@require_cpu
		def 					SCREAMING_SNAKE_CASE__   (self :		Any):
							debug_launcher(test_sync.main     ,     num_processes=1)


		@require_cpu
		def 					SCREAMING_SNAKE_CASE__   (self :		int):
							debug_launcher(test_sync.main)


		@require_single_gpu
		def 					SCREAMING_SNAKE_CASE__   (self :		Any):
							test_sync.main()


		@require_multi_gpu
		def 					SCREAMING_SNAKE_CASE__   (self :		Optional[Any]):
							print(F"""Found {torch.cuda.device_count()} devices.""")
							A			=					["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())











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 					snake_case					(							A			)							->							Optional[TaskTemplate]:




	'''simple docstring'''


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