




'''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    ):
							lowercase_							=				MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
							lowercase_							=				TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING







							def    __lowerCAmelCase			(  self       :  int							,			lowerCAmelCase_       :  Tuple							,			lowerCAmelCase_       :  Optional[Any]							,			lowerCAmelCase_       :  Any					)			->							int:


														"""simple docstring"""


														if isinstance(model.config							,			lowerCAmelCase_					):
																					_a     ,							_a	     =				list(tokenizer.lang_code_to_id.keys()					)[:2]
																					_a	     =				TranslationPipeline(model=lowerCAmelCase_							,			tokenizer=lowerCAmelCase_							,			src_lang=lowerCAmelCase_							,			tgt_lang=lowerCAmelCase_					)
														else:
																					_a	     =				TranslationPipeline(model=lowerCAmelCase_							,			tokenizer=lowerCAmelCase_					)
														return translator, ["Some string", "Some other text"]







							def    __lowerCAmelCase			(  self       :  str							,			lowerCAmelCase_       :  Tuple							,			lowerCAmelCase_       :  Dict					)			->							str:


														"""simple docstring"""


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

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

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







							@require_torch
							def    __lowerCAmelCase			(  self       :  List[str]					)			->							List[Any]:


														"""simple docstring"""


														_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(
														    lowerCAmelCase_							,			[
														        {
														            '''translation_text''': (
														                '''Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide'''
														                ''' Beide Beide'''
														            )
														        }
														    ]							,			)







							@require_tf
							def    __lowerCAmelCase			(  self       :  List[Any]					)			->							Dict:


														"""simple docstring"""


														_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(
														    lowerCAmelCase_							,			[
														        {
														            '''translation_text''': (
														                '''Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide Beide'''
														                ''' Beide Beide'''
														            )
														        }
														    ]							,			)







							@require_torch
							def    __lowerCAmelCase			(  self       :  int					)			->							Optional[int]:


														"""simple docstring"""


														_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(
														    lowerCAmelCase_							,			[
														        {
														            '''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       :  List[str]					)			->							List[Any]:


														"""simple docstring"""


														_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(
														    lowerCAmelCase_							,			[
														        {
														            '''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    ):







							@require_torch
							@slow
							def    __lowerCAmelCase			(  self       :  List[Any]					)			->							Optional[int]:


														"""simple docstring"""


														with self.assertRaises(lowerCAmelCase_					):
																					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    __lowerCAmelCase			(  self       :  Dict					)			->							Tuple:


														"""simple docstring"""


														_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=lowerCAmelCase_							,			tokenizer=lowerCAmelCase_					)
														# Missing src_lang, tgt_lang
														with self.assertRaises(lowerCAmelCase_					):
																					translator('''This is a test'''					)

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

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

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







							@require_torch
							def    __lowerCAmelCase			(  self       :  Optional[int]					)			->							Optional[int]:


														"""simple docstring"""


														_a	     =				'''patrickvonplaten/t5-tiny-random'''
														_a	     =				pipeline(task='''translation_cn_to_ar'''							,			model=lowerCAmelCase_					)
														self.assertEqual(translator._preprocess_params['''src_lang''']							,			'''cn'''					)
														self.assertEqual(translator._preprocess_params['''tgt_lang''']							,			'''ar'''					)







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


														"""simple docstring"""


														_a	     =				'''patrickvonplaten/t5-tiny-random'''
														with pytest.warns(lowerCAmelCase_							,			match=R'''.*translation_en_to_de.*'''					):
																					_a	     =				pipeline(task='''translation'''							,			model=lowerCAmelCase_					)
														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       :  Any					)			->							Tuple:


														"""simple docstring"""


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







'''simple docstring'''


def 		snake_case_    (UpperCamelCase       :  List[str] ,						UpperCamelCase       :  List[Any] ,						UpperCamelCase       :  Union[str, Any]      ):





							'''simple docstring'''


							_a	     =				index
							_a	     =				2 * index + 1
							_a	     =				2 * index + 2
							if left_index < heap_size and unsorted[left_index] > unsorted[largest]:
														_a	     =				left_index

							if right_index < heap_size and unsorted[right_index] > unsorted[largest]:
														_a	     =				right_index

							if largest != index:
														_a     ,							_a	     =				unsorted[index], unsorted[largest]
														heapify(UpperCamelCase ,						UpperCamelCase ,						UpperCamelCase      )
def 		snake_case_    (UpperCamelCase       :  Union[str, Any]      ):





							'''simple docstring'''


							_a	     =				len(UpperCamelCase      )
							for i in range(n // 2 - 1 ,						-1 ,						-1      ):
														heapify(UpperCamelCase ,						UpperCamelCase ,						UpperCamelCase      )
							for i in range(n - 1 ,						0 ,						-1      ):
														_a     ,							_a	     =				unsorted[i], unsorted[0]
														heapify(UpperCamelCase ,						0 ,						UpperCamelCase      )
							return unsorted


if __name__ == "__main__":
				_snake_case      :      int   							=		input('Enter numbers separated by a comma:\n').strip()
				_snake_case      :      Optional[Any]   							=		[int(item) for item in user_input.split(',')]
				print(heap_sort(unsorted))

