
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        lowerCAmelCase__ (				self     ,						UpperCamelCase     ,						UpperCamelCase     ,						UpperCamelCase) ->	Union[str, Any]:
										if isinstance(model.config     ,						UpperCamelCase):
													UpperCamelCase__   ,			UpperCamelCase__    :		Optional[Any]     =				list(tokenizer.lang_code_to_id.keys())[:2]
													UpperCamelCase__    :		str     =				TranslationPipeline(model=UpperCamelCase     ,						tokenizer=UpperCamelCase     ,						src_lang=UpperCamelCase     ,						tgt_lang=UpperCamelCase)
										else:
													UpperCamelCase__    :		Optional[int]     =				TranslationPipeline(model=UpperCamelCase     ,						tokenizer=UpperCamelCase)
										return translator, ["Some string", "Some other text"]
							def        lowerCAmelCase__ (				self     ,						UpperCamelCase     ,						UpperCamelCase) ->	Dict:
										UpperCamelCase__    :		List[Any]     =				translator('Some string')
										self.assertEqual(UpperCamelCase     ,						[{'translation_text': ANY(UpperCamelCase)}])

										UpperCamelCase__    :		int     =				translator(['Some string'])
										self.assertEqual(UpperCamelCase     ,						[{'translation_text': ANY(UpperCamelCase)}])

										UpperCamelCase__    :		Union[str, Any]     =				translator(['Some string', 'other string'])
										self.assertEqual(UpperCamelCase     ,						[{'translation_text': ANY(UpperCamelCase)}, {'translation_text': ANY(UpperCamelCase)}])
							@require_torch
							def        lowerCAmelCase__ (				self) ->	Optional[int]:
										UpperCamelCase__    :		Any     =				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(
										    UpperCamelCase     ,						[
										        {
										            'translation_text': (
										                'Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide'
										                ' Beide Beide'
										            )
										        }
										    ]     ,						)
							@require_tf
							def        lowerCAmelCase__ (				self) ->	int:
										UpperCamelCase__    :		int     =				pipeline('translation_en_to_ro'     ,						model='patrickvonplaten/t5-tiny-random'     ,						framework='tf')
										UpperCamelCase__    :		Optional[Any]     =				translator('This is a test string'     ,						max_length=20)
										self.assertEqual(
										    UpperCamelCase     ,						[
										        {
										            'translation_text': (
										                'Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide'
										                ' Beide Beide'
										            )
										        }
										    ]     ,						)
							@require_torch
							def        lowerCAmelCase__ (				self) ->	Dict:
										UpperCamelCase__    :		Tuple     =				pipeline('translation_en_to_de'     ,						model='patrickvonplaten/t5-tiny-random'     ,						framework='pt')
										UpperCamelCase__    :		Tuple     =				translator('This is a test string'     ,						max_length=20)
										self.assertEqual(
										    UpperCamelCase     ,						[
										        {
										            'translation_text': (
										                'monoton monoton monoton monoton monoton monoton monoton monoton monoton monoton urine urine'
										                ' urine urine urine urine urine urine urine'
										            )
										        }
										    ]     ,						)






							@require_tf
							def        lowerCAmelCase__ (				self) ->	Tuple:
										UpperCamelCase__    :		Optional[int]     =				pipeline('translation_en_to_de'     ,						model='patrickvonplaten/t5-tiny-random'     ,						framework='tf')
										UpperCamelCase__    :		List[Any]     =				translator('This is a test string'     ,						max_length=20)
										self.assertEqual(
										    UpperCamelCase     ,						[
										        {
										            '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        lowerCAmelCase__ (				self) ->	str:
										# We don't provide a default for this pair
										with self.assertRaises(UpperCamelCase):
													pipeline(task='translation_cn_to_ar')

										# but we do for this one
										UpperCamelCase__    :		int     =				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        lowerCAmelCase__ (				self) ->	List[str]:
										UpperCamelCase__    :		Dict     =				MBartForConditionalGeneration.from_pretrained('facebook/mbart-large-50-many-to-many-mmt')
										UpperCamelCase__    :		int     =				MBartaaTokenizerFast.from_pretrained('facebook/mbart-large-50-many-to-many-mmt')

										UpperCamelCase__    :		Optional[Any]     =				pipeline(task='translation'     ,						model=UpperCamelCase     ,						tokenizer=UpperCamelCase)
										# Missing src_lang, tgt_lang
										with self.assertRaises(UpperCamelCase):
													translator('This is a test')

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

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

										# src_lang, tgt_lang can be defined at pipeline call time
										UpperCamelCase__    :		List[Any]     =				pipeline(task='translation'     ,						model=UpperCamelCase     ,						tokenizer=UpperCamelCase     ,						src_lang='en_XX'     ,						tgt_lang='ar_AR')
										UpperCamelCase__    :		Any     =				translator('This is a test')
										self.assertEqual(UpperCamelCase     ,						[{'translation_text': 'هذا إختبار'}])
							@require_torch
							def        lowerCAmelCase__ (				self) ->	int:
										UpperCamelCase__    :		int     =				'patrickvonplaten/t5-tiny-random'
										UpperCamelCase__    :		Tuple     =				pipeline(task='translation_cn_to_ar'     ,						model=UpperCamelCase)
										self.assertEqual(translator._preprocess_params['src_lang']     ,						'cn')
										self.assertEqual(translator._preprocess_params['tgt_lang']     ,						'ar')
							@require_torch
							def        lowerCAmelCase__ (				self) ->	Any:
										UpperCamelCase__    :		Dict     =				'patrickvonplaten/t5-tiny-random'
										with pytest.warns(UpperCamelCase     ,						match=r'.*translation_en_to_de.*'):
													UpperCamelCase__    :		Tuple     =				pipeline(task='translation'     ,						model=UpperCamelCase)
										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        lowerCAmelCase__ (				self) ->	Dict:
										with self.assertRaises(UpperCamelCase):
													pipeline(task='translation')





import numpy as np

UpperCAmelCase__				:  str       					=				[
    ['''a''', '''b''', '''c''', '''d''', '''e'''],
    ['''f''', '''g''', '''h''', '''i''', '''k'''],
    ['''l''', '''m''', '''n''', '''o''', '''p'''],
    ['''q''', '''r''', '''s''', '''t''', '''u'''],
    ['''v''', '''w''', '''x''', '''y''', '''z'''],
]



class 			UpperCamelCase_			:




							'''simple docstring'''

							def __init__(				self) ->	None:
										UpperCamelCase__    :		Any     =				np.array(UpperCamelCase)
							def        lowerCAmelCase__ (				self     ,						UpperCamelCase) ->	np.ndarray:
										UpperCamelCase__   ,			UpperCamelCase__    :		Optional[int]     =				np.where(letter == self.SQUARE)
										UpperCamelCase__    :		int     =				np.concatenate([indexa + 1, indexa + 1])
										return indexes
							def        lowerCAmelCase__ (				self     ,						UpperCamelCase     ,						UpperCamelCase) ->	str:
										return self.SQUARE[indexa - 1, indexa - 1]
							def        lowerCAmelCase__ (				self     ,						UpperCamelCase) ->	str:
										UpperCamelCase__    :		str     =				message.lower()
										UpperCamelCase__    :		int     =				message.replace('j'     ,						'i')

										UpperCamelCase__    :		List[Any]     =				''
										for letter_index in range(len(UpperCamelCase)):
													if message[letter_index] != " ":
																UpperCamelCase__    :		Union[str, Any]     =				self.letter_to_numbers(message[letter_index])
																UpperCamelCase__    :		int     =				encoded_message + str(numbers[0]) + str(numbers[1])
													elif message[letter_index] == " ":
																UpperCamelCase__    :		str     =				encoded_message + ' '

										return encoded_message






							def        lowerCAmelCase__ (				self     ,						UpperCamelCase) ->	str:
										UpperCamelCase__    :		Union[str, Any]     =				message.replace(' '     ,						'  ')
										UpperCamelCase__    :		int     =				''
										for numbers_index in range(int(len(UpperCamelCase) / 2)):
													if message[numbers_index * 2] != " ":
																UpperCamelCase__    :		List[str]     =				message[numbers_index * 2]
																UpperCamelCase__    :		Tuple     =				message[numbers_index * 2 + 1]

																UpperCamelCase__    :		Tuple     =				self.numbers_to_letter(int(UpperCamelCase)     ,						int(UpperCamelCase))
																UpperCamelCase__    :		List[str]     =				decoded_message + letter
													elif message[numbers_index * 2] == " ":
																UpperCamelCase__    :		str     =				decoded_message + ' '

										return decoded_message



