


import os
import unittest

import pytest
from parameterized import parameterized

from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device


# skipping in unittest tests

__UpperCamelCase      						=    [(1,)]
def     UpperCamelCase_(			)->						Optional[Any]:
			UpperCamelCase__   =    bool(os.getenv("RUN_SLOW"			,       0					)					)
			if run_slow:
						assert True
			else:
						assert False, "should have been skipped"
def     UpperCamelCase_(			)->						Union[str, Any]:
			UpperCamelCase__   =    bool(os.getenv("RUN_SLOW"			,       0					)					)
			if run_slow and torch_device == "cuda":
						assert True
			else:
						assert False, "should have been skipped"







@require_torch
class     lowerCamelCase__		(							unittest.TestCase ):






			"""simple docstring"""






			@slow
			@require_torch_gpu
			def 			snake_case__			(							self       ):

						'''simple docstring'''


						check_slow_torch_cuda()




			@require_torch_gpu
			@slow
			def 			snake_case__			(							self       ):

						'''simple docstring'''


						check_slow_torch_cuda()







			@parameterized.expand(snake_case       )
			@slow
			def 			snake_case__			(							self ,  snake_case=None       ):

						'''simple docstring'''


						check_slow()



@slow
@require_torch_gpu
def     UpperCamelCase_(			)->						Any:
			check_slow_torch_cuda()
@require_torch_gpu
@slow
def     UpperCamelCase_(			)->						List[str]:
			check_slow_torch_cuda()
@slow
@pytest.mark.parametrize("param"			,       [1]					)
def     UpperCamelCase_(			_A				:Union[str, Any]					)->						List[str]:
			check_slow()







@pytest.mark.parametrize("param"			,       [1]					)
@slow
def     UpperCamelCase_(			_A				:Optional[int]					)->						Dict:
			check_slow()






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     UpperCamelCase_(			_A				:dict					)->						Optional[TaskTemplate]:
			UpperCamelCase__   =    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
			UpperCamelCase__   =    NAMEaTEMPLATE.get(_A					)
			return template.from_dict(_A					)


