





import gc
import unittest

from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
    is_pipeline_test,
    is_torch_available,
    nested_simplify,
    require_tf,
    require_torch,
    require_torch_gpu,
    slow,
)

from .test_pipelines_common import ANY





@is_pipeline_test
class 				A_				(      unittest.TestCase	):







							"""simple docstring"""





							SCREAMING_SNAKE_CASE_      : Any      =  MODEL_FOR_MASKED_LM_MAPPING
							SCREAMING_SNAKE_CASE_      : Dict      =  TF_MODEL_FOR_MASKED_LM_MAPPING







							def    __UpperCAmelCase (    self	:	Union[str, Any]  )						->					List[Any]:
									super().tearDown()
									# clean-up as much as possible GPU memory occupied by PyTorch
									gc.collect()
									if is_torch_available():
											import torch

											torch.cuda.empty_cache()







							@require_tf
							def    __UpperCAmelCase (    self	:	Tuple  )						->					List[Any]:
									_lowercase							= pipeline(task='fill-mask'						,model='sshleifer/tiny-distilroberta-base'						,top_k=2						,framework='tf'  )
									_lowercase							= unmasker('My name is <mask>'  )
									self.assertEqual(
									    nested_simplify(lowercase_						,decimals=6  )						,[
									        {'sequence': 'My name is grouped', 'score': 2.1e-05, 'token': 3_8015, 'token_str': ' grouped'},
									        {'sequence': 'My name is accuser', 'score': 2.1e-05, 'token': 2_5506, 'token_str': ' accuser'},
									    ]						,)

									_lowercase							= unmasker('The largest city in France is <mask>'  )
									self.assertEqual(
									    nested_simplify(lowercase_						,decimals=6  )						,[
									        {
									            'sequence': 'The largest city in France is grouped',
									            'score': 2.1e-05,
									            'token': 3_8015,
									            'token_str': ' grouped',
									        },
									        {
									            'sequence': 'The largest city in France is accuser',
									            'score': 2.1e-05,
									            'token': 2_5506,
									            'token_str': ' accuser',
									        },
									    ]						,)

									_lowercase							= unmasker('My name is <mask>'						,targets=[' Patrick', ' Clara', ' Teven']						,top_k=3  )
									self.assertEqual(
									    nested_simplify(lowercase_						,decimals=6  )						,[
									        {'sequence': 'My name is Clara', 'score': 2e-05, 'token': 1_3606, 'token_str': ' Clara'},
									        {'sequence': 'My name is Patrick', 'score': 2e-05, 'token': 3499, 'token_str': ' Patrick'},
									        {'sequence': 'My name is Te', 'score': 1.9e-05, 'token': 2941, 'token_str': ' Te'},
									    ]						,)







							@require_torch
							def    __UpperCAmelCase (    self	:	Union[str, Any]  )						->					Any:
									_lowercase							= pipeline(task='fill-mask'						,model='sshleifer/tiny-distilroberta-base'						,top_k=2						,framework='pt'  )

									_lowercase							= unmasker('My name is <mask>'  )
									self.assertEqual(
									    nested_simplify(lowercase_						,decimals=6  )						,[
									        {'sequence': 'My name is Maul', 'score': 2.2e-05, 'token': 3_5676, 'token_str': ' Maul'},
									        {'sequence': 'My name isELS', 'score': 2.2e-05, 'token': 1_6416, 'token_str': 'ELS'},
									    ]						,)

									_lowercase							= unmasker('The largest city in France is <mask>'  )
									self.assertEqual(
									    nested_simplify(lowercase_						,decimals=6  )						,[
									        {
									            'sequence': 'The largest city in France is Maul',
									            'score': 2.2e-05,
									            'token': 3_5676,
									            'token_str': ' Maul',
									        },
									        {'sequence': 'The largest city in France isELS', 'score': 2.2e-05, 'token': 1_6416, 'token_str': 'ELS'},
									    ]						,)

									_lowercase							= unmasker('My name is <mask>'						,targets=[' Patrick', ' Clara', ' Teven']						,top_k=3  )
									self.assertEqual(
									    nested_simplify(lowercase_						,decimals=6  )						,[
									        {'sequence': 'My name is Patrick', 'score': 2.1e-05, 'token': 3499, 'token_str': ' Patrick'},
									        {'sequence': 'My name is Te', 'score': 2e-05, 'token': 2941, 'token_str': ' Te'},
									        {'sequence': 'My name is Clara', 'score': 2e-05, 'token': 1_3606, 'token_str': ' Clara'},
									    ]						,)

									_lowercase							= unmasker('My name is <mask> <mask>'						,top_k=2  )

									self.assertEqual(
									    nested_simplify(lowercase_						,decimals=6  )						,[
									        [
									            {
									                'score': 2.2e-05,
									                'token': 3_5676,
									                'token_str': ' Maul',
									                'sequence': '<s>My name is Maul<mask></s>',
									            },
									            {'score': 2.2e-05, 'token': 1_6416, 'token_str': 'ELS', 'sequence': '<s>My name isELS<mask></s>'},
									        ],
									        [
									            {
									                'score': 2.2e-05,
									                'token': 3_5676,
									                'token_str': ' Maul',
									                'sequence': '<s>My name is<mask> Maul</s>',
									            },
									            {'score': 2.2e-05, 'token': 1_6416, 'token_str': 'ELS', 'sequence': '<s>My name is<mask>ELS</s>'},
									        ],
									    ]						,)







							@require_torch_gpu
							def    __UpperCAmelCase (    self	:	Tuple  )						->					Union[str, Any]:
									_lowercase							= pipeline('fill-mask'						,model='hf-internal-testing/tiny-random-distilbert'						,device=0						,framework='pt'  )

									# convert model to fp16
									pipe.model.half()

									_lowercase							= pipe('Paris is the [MASK] of France.'  )
									# We actually don't care about the result, we just want to make sure
									# it works, meaning the float16 tensor got casted back to float32
									# for postprocessing.
									self.assertIsInstance(lowercase_						,lowercase_  )







							@slow
							@require_torch
							def    __UpperCAmelCase (    self	:	List[Any]  )						->					List[Any]:
									_lowercase							= pipeline(task='fill-mask'						,model='distilroberta-base'						,top_k=2						,framework='pt'  )
									self.run_large_test(lowercase_  )







							@slow
							@require_tf
							def    __UpperCAmelCase (    self	:	List[str]  )						->					List[str]:
									_lowercase							= pipeline(task='fill-mask'						,model='distilroberta-base'						,top_k=2						,framework='tf'  )
									self.run_large_test(lowercase_  )







							def    __UpperCAmelCase (    self	:	Optional[Any]						,__A	:	int  )						->					Any:
									_lowercase							= unmasker('My name is <mask>'  )
									self.assertEqual(
									    nested_simplify(lowercase_  )						,[
									        {'sequence': 'My name is John', 'score': 0.008, 'token': 610, 'token_str': ' John'},
									        {'sequence': 'My name is Chris', 'score': 0.007, 'token': 1573, 'token_str': ' Chris'},
									    ]						,)
									_lowercase							= unmasker('The largest city in France is <mask>'  )
									self.assertEqual(
									    nested_simplify(lowercase_  )						,[
									        {
									            'sequence': 'The largest city in France is Paris',
									            'score': 0.251,
									            'token': 2201,
									            'token_str': ' Paris',
									        },
									        {
									            'sequence': 'The largest city in France is Lyon',
									            'score': 0.214,
									            'token': 1_2790,
									            'token_str': ' Lyon',
									        },
									    ]						,)

									_lowercase							= unmasker('My name is <mask>'						,targets=[' Patrick', ' Clara', ' Teven']						,top_k=3  )
									self.assertEqual(
									    nested_simplify(lowercase_  )						,[
									        {'sequence': 'My name is Patrick', 'score': 0.005, 'token': 3499, 'token_str': ' Patrick'},
									        {'sequence': 'My name is Clara', 'score': 0.000, 'token': 1_3606, 'token_str': ' Clara'},
									        {'sequence': 'My name is Te', 'score': 0.000, 'token': 2941, 'token_str': ' Te'},
									    ]						,)







							@require_torch
							def    __UpperCAmelCase (    self	:	Union[str, Any]  )						->					str:
									_lowercase							= pipeline(task='fill-mask'						,model='sshleifer/tiny-distilroberta-base'						,framework='pt'  )
									_lowercase							= None
									_lowercase							= None
									self.run_pipeline_test(lowercase_						,[]  )







							@require_tf
							def    __UpperCAmelCase (    self	:	Optional[Any]  )						->					List[str]:
									_lowercase							= pipeline(task='fill-mask'						,model='sshleifer/tiny-distilroberta-base'						,framework='tf'  )
									_lowercase							= None
									_lowercase							= None
									self.run_pipeline_test(lowercase_						,[]  )







							def    __UpperCAmelCase (    self	:	Optional[int]						,__A	:	Union[str, Any]						,__A	:	Tuple						,__A	:	Optional[int]  )						->					int:







									if tokenizer is None or tokenizer.mask_token_id is None:
											self.skipTest('The provided tokenizer has no mask token, (probably reformer or wav2vec2)'  )

									_lowercase							= FillMaskPipeline(model=lowercase_						,tokenizer=lowercase_  )
									_lowercase							= [
									    F"""This is another {tokenizer.mask_token} test""",
									]
									return fill_masker, examples







							def    __UpperCAmelCase (    self	:	Optional[Any]						,__A	:	Optional[Any]						,__A	:	Optional[int]  )						->					str:
									_lowercase							= fill_masker.tokenizer
									_lowercase							= fill_masker.model

									_lowercase							= fill_masker(
									    F"""This is a {tokenizer.mask_token}"""						,)
									self.assertEqual(
									    lowercase_						,[
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									    ]						,)

									_lowercase							= fill_masker([F"""This is a {tokenizer.mask_token}"""]  )
									self.assertEqual(
									    lowercase_						,[
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									    ]						,)

									_lowercase							= fill_masker([F"""This is a {tokenizer.mask_token}""", F"""Another {tokenizer.mask_token} great test."""]  )
									self.assertEqual(
									    lowercase_						,[
									        [
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        ],
									        [
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        ],
									    ]						,)

									with self.assertRaises(lowercase_  ):
											fill_masker([None]  )
									# No mask_token is not supported
									with self.assertRaises(lowercase_  ):
											fill_masker('This is'  )

									self.run_test_top_k(lowercase_						,lowercase_  )
									self.run_test_targets(lowercase_						,lowercase_  )
									self.run_test_top_k_targets(lowercase_						,lowercase_  )
									self.fill_mask_with_duplicate_targets_and_top_k(lowercase_						,lowercase_  )
									self.fill_mask_with_multiple_masks(lowercase_						,lowercase_  )







							def    __UpperCAmelCase (    self	:	int						,__A	:	Dict						,__A	:	List[str]  )						->					Union[str, Any]:
									_lowercase							= tokenizer.get_vocab()
									_lowercase							= sorted(vocab.keys()  )[:2]
									# Pipeline argument
									_lowercase							= FillMaskPipeline(model=lowercase_						,tokenizer=lowercase_						,targets=lowercase_  )
									_lowercase							= fill_masker(F"""This is a {tokenizer.mask_token}"""  )
									self.assertEqual(
									    lowercase_						,[
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									    ]						,)
									_lowercase							= {vocab[el] for el in targets}
									self.assertEqual({el['token'] for el in outputs}						,lowercase_  )
									_lowercase							= [tokenizer.decode([x]  ) for x in target_ids]
									self.assertEqual({el['token_str'] for el in outputs}						,set(lowercase_  )  )

									# Call argument
									_lowercase							= FillMaskPipeline(model=lowercase_						,tokenizer=lowercase_  )
									_lowercase							= fill_masker(F"""This is a {tokenizer.mask_token}"""						,targets=lowercase_  )
									self.assertEqual(
									    lowercase_						,[
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									    ]						,)
									_lowercase							= {vocab[el] for el in targets}
									self.assertEqual({el['token'] for el in outputs}						,lowercase_  )
									_lowercase							= [tokenizer.decode([x]  ) for x in target_ids]
									self.assertEqual({el['token_str'] for el in outputs}						,set(lowercase_  )  )

									# Score equivalence
									_lowercase							= fill_masker(F"""This is a {tokenizer.mask_token}"""						,targets=lowercase_  )
									_lowercase							= [top_mask['token_str'] for top_mask in outputs]
									_lowercase							= [top_mask['score'] for top_mask in outputs]

									# For some BPE tokenizers, `</w>` is removed during decoding, so `token_str` won't be the same as in `targets`.
									if set(lowercase_  ) == set(lowercase_  ):
											_lowercase							= fill_masker(F"""This is a {tokenizer.mask_token}"""						,targets=lowercase_  )
											_lowercase							= [top_mask['score'] for top_mask in unmasked_targets]
											self.assertEqual(nested_simplify(lowercase_  )						,nested_simplify(lowercase_  )  )

									# Raises with invalid
									with self.assertRaises(lowercase_  ):
											_lowercase							= fill_masker(F"""This is a {tokenizer.mask_token}"""						,targets=[]  )
									# For some tokenizers, `""` is actually in the vocabulary and the expected error won't raised
									if "" not in tokenizer.get_vocab():
											with self.assertRaises(lowercase_  ):
													_lowercase							= fill_masker(F"""This is a {tokenizer.mask_token}"""						,targets=['']  )
											with self.assertRaises(lowercase_  ):
													_lowercase							= fill_masker(F"""This is a {tokenizer.mask_token}"""						,targets=''  )







							def    __UpperCAmelCase (    self	:	Union[str, Any]						,__A	:	str						,__A	:	List[str]  )						->					Any:
									_lowercase							= FillMaskPipeline(model=lowercase_						,tokenizer=lowercase_						,top_k=2  )
									_lowercase							= fill_masker(F"""This is a {tokenizer.mask_token}"""  )
									self.assertEqual(
									    lowercase_						,[
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									    ]						,)

									_lowercase							= FillMaskPipeline(model=lowercase_						,tokenizer=lowercase_  )
									_lowercase							= fill_masker(F"""This is a {tokenizer.mask_token}"""						,top_k=2  )
									self.assertEqual(
									    lowercase_						,[
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									    ]						,)
									self.assertEqual(nested_simplify(lowercase_  )						,nested_simplify(lowercase_  )  )







							def    __UpperCAmelCase (    self	:	Any						,__A	:	Union[str, Any]						,__A	:	Tuple  )						->					Union[str, Any]:
									_lowercase							= tokenizer.get_vocab()
									_lowercase							= FillMaskPipeline(model=lowercase_						,tokenizer=lowercase_  )

									# top_k=2, ntargets=3
									_lowercase							= sorted(vocab.keys()  )[:3]
									_lowercase							= fill_masker(F"""This is a {tokenizer.mask_token}"""						,top_k=2						,targets=lowercase_  )

									# If we use the most probably targets, and filter differently, we should still
									# have the same results
									_lowercase							= [el['token_str'] for el in sorted(lowercase_						,key=lambda __A  : x["score"]						,reverse=lowercase_  )]
									# For some BPE tokenizers, `</w>` is removed during decoding, so `token_str` won't be the same as in `targets`.
									if set(lowercase_  ).issubset(lowercase_  ):
											_lowercase							= fill_masker(F"""This is a {tokenizer.mask_token}"""						,top_k=3						,targets=lowercase_  )
											# They should yield exactly the same result
											self.assertEqual(nested_simplify(lowercase_  )						,nested_simplify(lowercase_  )  )







							def    __UpperCAmelCase (    self	:	int						,__A	:	Optional[int]						,__A	:	List[str]  )						->					Tuple:
									_lowercase							= FillMaskPipeline(model=lowercase_						,tokenizer=lowercase_  )
									_lowercase							= tokenizer.get_vocab()
									# String duplicates + id duplicates
									_lowercase							= sorted(vocab.keys()  )[:3]
									_lowercase							= [targets[0], targets[1], targets[0], targets[2], targets[1]]
									_lowercase							= fill_masker(F"""My name is {tokenizer.mask_token}"""						,targets=lowercase_						,top_k=10  )

									# The target list contains duplicates, so we can't output more
									# than them
									self.assertEqual(len(lowercase_  )						,3  )







							def    __UpperCAmelCase (    self	:	Union[str, Any]						,__A	:	List[str]						,__A	:	Any  )						->					Dict:
									_lowercase							= FillMaskPipeline(model=lowercase_						,tokenizer=lowercase_  )

									_lowercase							= fill_masker(
									    F"""This is a {tokenizer.mask_token} {tokenizer.mask_token} {tokenizer.mask_token}"""						,top_k=2  )
									self.assertEqual(
									    lowercase_						,[
									        [
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        ],
									        [
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        ],
									        [
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									            {'sequence': ANY(lowercase_  ), 'score': ANY(lowercase_  ), 'token': ANY(lowercase_  ), 'token_str': ANY(lowercase_  )},
									        ],
									    ]						,)






def 							SCREAMING_SNAKE_CASE__       (  snake_case__  :List[str]     )      ->						Dict:
  _lowercase							= len(snake_case__     )
  while cur > 1:
    # Find the maximum number in arr
    _lowercase							= arr.index(max(arr[0:cur]     )     )
    # Reverse from 0 to mi
    _lowercase							= arr[mi::-1] + arr[mi + 1 : len(snake_case__     )]
    # Reverse whole list
    _lowercase							= arr[cur - 1 :: -1] + arr[cur : len(snake_case__     )]
    cur -= 1
  return arr


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