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      lowercase_						(						unittest.TestCase		):



	"""simple docstring"""





	UpperCAmelCase_						:      Any     =       MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
	UpperCAmelCase_						:      Union[str, Any]     =       TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING


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


	def     SCREAMING_SNAKE_CASE_       (							self	,    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE       )		->Optional[Any]:
								lowerCAmelCase				=	translator('''Some string'''       )
								self.assertEqual(__SCREAMING_SNAKE_CASE	,    [{'''translation_text''': ANY(__SCREAMING_SNAKE_CASE       )}]       )

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

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


	@require_torch
	def     SCREAMING_SNAKE_CASE_       (							self       )		->Any:
								lowerCAmelCase				=	pipeline('''translation_en_to_ro'''	,    model='''patrickvonplaten/t5-tiny-random'''	,    framework='''pt'''       )
								lowerCAmelCase				=	translator('''This is a test string'''	,    max_length=20       )
								self.assertEqual(
								    __SCREAMING_SNAKE_CASE	,    [
								        {
								            '''translation_text''': (
								                '''Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide'''
								                ''' Beide Beide'''
								            )
								        }
								    ]	,    )


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


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




	@require_tf
	def     SCREAMING_SNAKE_CASE_       (							self       )		->Dict:
								lowerCAmelCase				=	pipeline('''translation_en_to_de'''	,    model='''patrickvonplaten/t5-tiny-random'''	,    framework='''tf'''       )
								lowerCAmelCase				=	translator('''This is a test string'''	,    max_length=20       )
								self.assertEqual(
								    __SCREAMING_SNAKE_CASE	,    [
								        {
								            '''translation_text''': (
								                '''monoton monoton monoton monoton monoton monoton monoton monoton monoton monoton urine urine'''
								                ''' urine urine urine urine urine urine urine'''
								            )
								        }
								    ]	,    )




class      lowercase_						(						unittest.TestCase		):



	"""simple docstring"""





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

								# but we do for this one
								lowerCAmelCase				=	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     SCREAMING_SNAKE_CASE_       (							self       )		->str:
								lowerCAmelCase				=	MBartForConditionalGeneration.from_pretrained('''facebook/mbart-large-50-many-to-many-mmt'''       )
								lowerCAmelCase				=	MBartaaTokenizerFast.from_pretrained('''facebook/mbart-large-50-many-to-many-mmt'''       )

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

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

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

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


	@require_torch
	def     SCREAMING_SNAKE_CASE_       (							self       )		->Dict:
								lowerCAmelCase				=	'''patrickvonplaten/t5-tiny-random'''
								lowerCAmelCase				=	pipeline(task='''translation_cn_to_ar'''	,    model=__SCREAMING_SNAKE_CASE       )
								self.assertEqual(translator._preprocess_params['''src_lang''']	,    '''cn'''       )
								self.assertEqual(translator._preprocess_params['''tgt_lang''']	,    '''ar'''       )


	@require_torch
	def     SCREAMING_SNAKE_CASE_       (							self       )		->Optional[int]:
								lowerCAmelCase				=	'''patrickvonplaten/t5-tiny-random'''
								with pytest.warns(__SCREAMING_SNAKE_CASE	,    match=R'''.*translation_en_to_de.*'''       ):
															lowerCAmelCase				=	pipeline(task='''translation'''	,    model=__SCREAMING_SNAKE_CASE       )
								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     SCREAMING_SNAKE_CASE_       (							self       )		->str:
								with self.assertRaises(__SCREAMING_SNAKE_CASE       ):
															pipeline(task='''translation'''       )




def      SCREAMING_SNAKE_CASE_  (		snake_case__     ,						snake_case__							)  ->			int:
							return (input_a, input_a).count(0							) % 2

def      SCREAMING_SNAKE_CASE_  (		)  ->			None:
							assert xor_gate(0     ,						0							) == 0
							assert xor_gate(0     ,						1							) == 1
							assert xor_gate(1     ,						0							) == 1
							assert xor_gate(1     ,						1							) == 0


if __name__ == "__main__":
	print(xor_gate(0, 0))
	print(xor_gate(0, 1))



