


"""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     A(     unittest.TestCase		):

		"""simple docstring"""





		A         =       MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
		A         =       TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
		def      _UpperCamelCase(   self				,							SCREAMING_SNAKE_CASE__				,							SCREAMING_SNAKE_CASE__				,							SCREAMING_SNAKE_CASE__      )			->  Optional[Any]:

					"""simple docstring"""



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

					"""simple docstring"""



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

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

					_UpperCamelCase				:str				    =  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      _UpperCamelCase(   self      )			->  Any:

					"""simple docstring"""



					_UpperCamelCase				:int				    =  pipeline('''translation_en_to_ro'''				,							model='''patrickvonplaten/t5-tiny-random'''				,							framework='''pt'''      )
					_UpperCamelCase				:List[str]				    =  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      _UpperCamelCase(   self      )			->  str:

					"""simple docstring"""



					_UpperCamelCase				:Tuple				    =  pipeline('''translation_en_to_ro'''				,							model='''patrickvonplaten/t5-tiny-random'''				,							framework='''tf'''      )
					_UpperCamelCase				:List[Any]				    =  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      _UpperCamelCase(   self      )			->  List[str]:

					"""simple docstring"""



					_UpperCamelCase				:Optional[Any]				    =  pipeline('''translation_en_to_de'''				,							model='''patrickvonplaten/t5-tiny-random'''				,							framework='''pt'''      )
					_UpperCamelCase				:Any				    =  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      _UpperCamelCase(   self      )			->  Dict:

					"""simple docstring"""



					_UpperCamelCase				:List[Any]				    =  pipeline('''translation_en_to_de'''				,							model='''patrickvonplaten/t5-tiny-random'''				,							framework='''tf'''      )
					_UpperCamelCase				:Dict				    =  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     A(     unittest.TestCase		):

		"""simple docstring"""





		@require_torch
		@slow
		def      _UpperCamelCase(   self      )			->  List[Any]:

					"""simple docstring"""



					with self.assertRaises(__SCREAMING_SNAKE_CASE      ):
								pipeline(task='''translation_cn_to_ar'''      )

					# but we do for this one
					_UpperCamelCase				:Optional[Any]				    =  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      _UpperCamelCase(   self      )			->  str:

					"""simple docstring"""



					_UpperCamelCase				:List[str]				    =  MBartForConditionalGeneration.from_pretrained('''facebook/mbart-large-50-many-to-many-mmt'''      )
					_UpperCamelCase				:Dict				    =  MBartaaTokenizerFast.from_pretrained('''facebook/mbart-large-50-many-to-many-mmt'''      )

					_UpperCamelCase				:Optional[int]				    =  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'''      )

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

					_UpperCamelCase				:Tuple				    =  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
					_UpperCamelCase				:str				    =  pipeline(task='''translation'''				,							model=__SCREAMING_SNAKE_CASE				,							tokenizer=__SCREAMING_SNAKE_CASE				,							src_lang='''en_XX'''				,							tgt_lang='''ar_AR'''      )
					_UpperCamelCase				:int				    =  translator('''This is a test'''      )
					self.assertEqual(__SCREAMING_SNAKE_CASE				,							[{'''translation_text''': '''هذا إختبار'''}]      )
		@require_torch
		def      _UpperCamelCase(   self      )			->  Dict:

					"""simple docstring"""



					_UpperCamelCase				:Dict				    =  '''patrickvonplaten/t5-tiny-random'''
					_UpperCamelCase				:Optional[int]				    =  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      _UpperCamelCase(   self      )			->  Optional[int]:

					"""simple docstring"""



					_UpperCamelCase				:Optional[int]				    =  '''patrickvonplaten/t5-tiny-random'''
					with pytest.warns(__SCREAMING_SNAKE_CASE				,							match=r'''.*translation_en_to_de.*'''      ):
								_UpperCamelCase				:Optional[Any]				    =  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      _UpperCamelCase(   self      )			->  str:

					"""simple docstring"""



					with self.assertRaises(__SCREAMING_SNAKE_CASE      ):
								pipeline(task='''translation'''      )





"""simple docstring"""






class     A:

		"""simple docstring"""





		def __init__(   self      )			->  List[str]:

					"""simple docstring"""



					_UpperCamelCase				:List[Any]				    =  []
					_UpperCamelCase				:Dict				    =  0
					_UpperCamelCase				:List[Any]				    =  0
		def __str__(   self      )			->  Optional[int]:

					"""simple docstring"""



					_UpperCamelCase				:Optional[Any]				    =  '''<''' + str(self.entries      )[1:-1] + '''>'''
					return printed
		def      _UpperCamelCase(   self				,							SCREAMING_SNAKE_CASE__      )			->  Tuple:

					"""simple docstring"""



					self.entries.append(SCREAMING_SNAKE_CASE__      )
					_UpperCamelCase				:Union[str, Any]				    =  self.length + 1
		def      _UpperCamelCase(   self      )			->  Dict:

					"""simple docstring"""



					_UpperCamelCase				:str				    =  self.length - 1
					_UpperCamelCase				:Optional[int]				    =  self.entries[self.front]
					# self.front-=1
					# self.entries = self.entries[self.front:]
					_UpperCamelCase				:Tuple				    =  self.entries[1:]
					return dequeued
		def      _UpperCamelCase(   self				,							SCREAMING_SNAKE_CASE__      )			->  str:

					"""simple docstring"""



					for _ in range(SCREAMING_SNAKE_CASE__      ):
								self.put(self.get()      )
		def      _UpperCamelCase(   self      )			->  str:

					"""simple docstring"""



					return self.entries[0]
		def      _UpperCamelCase(   self      )			->  Union[str, Any]:

					"""simple docstring"""



					return self.length

