




'''simple docstring'''
import unittest

import pytest

from transformers import (
    MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    MBartaaTokenizerFast,
    MBartConfig,
    MBartForConditionalGeneration,
    TranslationPipeline,
    pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch, slow

from .test_pipelines_common import ANY
@is_pipeline_test
class      __UpperCAmelCase							(    unittest.TestCase							):



					'''simple docstring'''





					_UpperCamelCase  	=		MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
					_UpperCamelCase  	=		TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING



					def 						__snake_case	(  self    :	List[Any]			,					_lowercase    :	str			,					_lowercase    :	List[Any]			,					_lowercase    :	List[str])						->       Optional[Any]:
								if isinstance(model.config			,					_lowercase):
											A_		,   A_       		=   list(tokenizer.lang_code_to_id.keys())[:2]
											A_       		=   TranslationPipeline(model=_lowercase			,					tokenizer=_lowercase			,					src_lang=_lowercase			,					tgt_lang=_lowercase)
								else:
											A_       		=   TranslationPipeline(model=_lowercase			,					tokenizer=_lowercase)
								return translator, ["Some string", "Some other text"]



					def 						__snake_case	(  self    :	List[str]			,					_lowercase    :	int			,					_lowercase    :	Union[str, Any])						->       List[str]:
								A_       		=   translator('Some string')
								self.assertEqual(_lowercase			,					[{'translation_text': ANY(_lowercase)}])

								A_       		=   translator(['Some string'])
								self.assertEqual(_lowercase			,					[{'translation_text': ANY(_lowercase)}])

								A_       		=   translator(['Some string', 'other string'])
								self.assertEqual(_lowercase			,					[{'translation_text': ANY(_lowercase)}, {'translation_text': ANY(_lowercase)}])



					@require_torch
					def 						__snake_case	(  self    :	Optional[int])						->       str:
								A_       		=   pipeline('translation_en_to_ro'			,					model='patrickvonplaten/t5-tiny-random'			,					framework='pt')
								A_       		=   translator('This is a test string'			,					max_length=20)
								self.assertEqual(
								    _lowercase			,					[
								        {
								            'translation_text': (
								                'Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide'
								                ' Beide Beide'
								            )
								        }
								    ]			,					)



					@require_tf
					def 						__snake_case	(  self    :	Any)						->       int:
								A_       		=   pipeline('translation_en_to_ro'			,					model='patrickvonplaten/t5-tiny-random'			,					framework='tf')
								A_       		=   translator('This is a test string'			,					max_length=20)
								self.assertEqual(
								    _lowercase			,					[
								        {
								            'translation_text': (
								                'Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide'
								                ' Beide Beide'
								            )
								        }
								    ]			,					)



					@require_torch
					def 						__snake_case	(  self    :	Dict)						->       str:
								A_       		=   pipeline('translation_en_to_de'			,					model='patrickvonplaten/t5-tiny-random'			,					framework='pt')
								A_       		=   translator('This is a test string'			,					max_length=20)
								self.assertEqual(
								    _lowercase			,					[
								        {
								            'translation_text': (
								                'monoton monoton monoton monoton monoton monoton monoton monoton monoton monoton urine urine'
								                ' urine urine urine urine urine urine urine'
								            )
								        }
								    ]			,					)



					@require_tf
					def 						__snake_case	(  self    :	Union[str, Any])						->       str:
								A_       		=   pipeline('translation_en_to_de'			,					model='patrickvonplaten/t5-tiny-random'			,					framework='tf')
								A_       		=   translator('This is a test string'			,					max_length=20)
								self.assertEqual(
								    _lowercase			,					[
								        {
								            'translation_text': (
								                'monoton monoton monoton monoton monoton monoton monoton monoton monoton monoton urine urine'
								                ' urine urine urine urine urine urine urine'
								            )
								        }
								    ]			,					)





class      __UpperCAmelCase							(    unittest.TestCase							):



					'''simple docstring'''





					@require_torch
					@slow
					def 						__snake_case	(  self    :	int)						->       List[str]:
								# We don't provide a default for this pair
								with self.assertRaises(_lowercase):
											pipeline(task='translation_cn_to_ar')

								# but we do for this one
								A_       		=   pipeline(task='translation_en_to_de')
								self.assertEqual(translator._preprocess_params['src_lang']			,					'en')
								self.assertEqual(translator._preprocess_params['tgt_lang']			,					'de')



					@require_torch
					@slow
					def 						__snake_case	(  self    :	List[Any])						->       Union[str, Any]:
								A_       		=   MBartForConditionalGeneration.from_pretrained('facebook/mbart-large-50-many-to-many-mmt')
								A_       		=   MBartaaTokenizerFast.from_pretrained('facebook/mbart-large-50-many-to-many-mmt')

								A_       		=   pipeline(task='translation'			,					model=_lowercase			,					tokenizer=_lowercase)
								# Missing src_lang, tgt_lang
								with self.assertRaises(_lowercase):
											translator('This is a test')

								A_       		=   translator('This is a test'			,					src_lang='en_XX'			,					tgt_lang='ar_AR')
								self.assertEqual(_lowercase			,					[{'translation_text': 'هذا إختبار'}])

								A_       		=   translator('This is a test'			,					src_lang='en_XX'			,					tgt_lang='hi_IN')
								self.assertEqual(_lowercase			,					[{'translation_text': 'यह एक परीक्षण है'}])

								# src_lang, tgt_lang can be defined at pipeline call time
								A_       		=   pipeline(task='translation'			,					model=_lowercase			,					tokenizer=_lowercase			,					src_lang='en_XX'			,					tgt_lang='ar_AR')
								A_       		=   translator('This is a test')
								self.assertEqual(_lowercase			,					[{'translation_text': 'هذا إختبار'}])



					@require_torch
					def 						__snake_case	(  self    :	int)						->       Any:
								A_       		=   'patrickvonplaten/t5-tiny-random'
								A_       		=   pipeline(task='translation_cn_to_ar'			,					model=_lowercase)
								self.assertEqual(translator._preprocess_params['src_lang']			,					'cn')
								self.assertEqual(translator._preprocess_params['tgt_lang']			,					'ar')



					@require_torch
					def 						__snake_case	(  self    :	str)						->       List[Any]:
								A_       		=   'patrickvonplaten/t5-tiny-random'
								with pytest.warns(_lowercase			,					match=r'.*translation_en_to_de.*'):
											A_       		=   pipeline(task='translation'			,					model=_lowercase)
								self.assertEqual(translator.task			,					'translation_en_to_de')
								self.assertEqual(translator._preprocess_params['src_lang']			,					'en')
								self.assertEqual(translator._preprocess_params['tgt_lang']			,					'de')



					@require_torch
					def 						__snake_case	(  self    :	Dict)						->       int:
								with self.assertRaises(_lowercase):
											pipeline(task='translation')










'''simple docstring'''
def  lowerCamelCase(       SCREAMING_SNAKE_CASE_    )		->		int:

			if not isinstance(SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    ) or number < 0:
						raise ValueError('Input must be a non-negative integer'    )

			A_       		=   number & ~(number - 1)
			A_       		=   0
			while intermediate:
						intermediate >>= 1
						index += 1
			return index - 1


if __name__ == "__main__":
							import doctest

							doctest.testmod(verbose=True)




