


'''simple docstring'''



import shutil
import tempfile
import unittest

from transformers import (
    SPIECE_UNDERLINE,
    AddedToken,
    BatchEncoding,
    NllbTokenizer,
    NllbTokenizerFast,
    is_torch_available,
)
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


__A						=get_tests_dir('fixtures/test_sentencepiece.model')


if is_torch_available():
		from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

__A						=25_60_47
__A						=25_61_45


@require_sentencepiece
@require_tokenizers
class 		_snake_case       (  SCREAMING_SNAKE_CASE__							, unittest.TestCase						):
					lowerCAmelCase   :List[Any]				=       NllbTokenizer
					lowerCAmelCase   :List[Any]				=       NllbTokenizerFast
					lowerCAmelCase   :List[str]				=       True
					lowerCAmelCase   :Dict				=       True
					lowerCAmelCase   :Optional[int]				=       {}




					def 					snake_case__    (   self):
								super().setUp()

								# We have a SentencePiece fixture for testing
								UpperCAmelCase__	:       Optional[int]   =  NllbTokenizer(A_				,				keep_accents=A_)
								tokenizer.save_pretrained(self.tmpdirname)




					def 					snake_case__    (   self):
								UpperCAmelCase__	:       Dict   =  NllbTokenizer(A_				,				keep_accents=A_)

								UpperCAmelCase__	:       Any   =  tokenizer.tokenize("""This is a test""")
								self.assertListEqual(A_				,				["""▁This""", """▁is""", """▁a""", """▁t""", """est"""])

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(A_)				,				[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]				,				)

								UpperCAmelCase__	:       Union[str, Any]   =  tokenizer.tokenize("""I was born in 92000, and this is falsé.""")
								self.assertListEqual(
								    A_				,				[
								        SPIECE_UNDERLINE + """I""",
								        SPIECE_UNDERLINE + """was""",
								        SPIECE_UNDERLINE + """b""",
								        """or""",
								        """n""",
								        SPIECE_UNDERLINE + """in""",
								        SPIECE_UNDERLINE + """""",
								        """9""",
								        """2""",
								        """0""",
								        """0""",
								        """0""",
								        """,""",
								        SPIECE_UNDERLINE + """and""",
								        SPIECE_UNDERLINE + """this""",
								        SPIECE_UNDERLINE + """is""",
								        SPIECE_UNDERLINE + """f""",
								        """al""",
								        """s""",
								        """é""",
								        """.""",
								    ]				,				)
								UpperCAmelCase__	:       List[Any]   =  tokenizer.convert_tokens_to_ids(A_)
								self.assertListEqual(
								    A_				,				[
								        value + tokenizer.fairseq_offset
								        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
								    ]				,				)

								UpperCAmelCase__	:       int   =  tokenizer.convert_ids_to_tokens(A_)
								self.assertListEqual(
								    A_				,				[
								        SPIECE_UNDERLINE + """I""",
								        SPIECE_UNDERLINE + """was""",
								        SPIECE_UNDERLINE + """b""",
								        """or""",
								        """n""",
								        SPIECE_UNDERLINE + """in""",
								        SPIECE_UNDERLINE + """""",
								        """<unk>""",
								        """2""",
								        """0""",
								        """0""",
								        """0""",
								        """,""",
								        SPIECE_UNDERLINE + """and""",
								        SPIECE_UNDERLINE + """this""",
								        SPIECE_UNDERLINE + """is""",
								        SPIECE_UNDERLINE + """f""",
								        """al""",
								        """s""",
								        """<unk>""",
								        """.""",
								    ]				,				)




					def 					snake_case__    (   self):
								UpperCAmelCase__	:       List[Any]   =  (self.rust_tokenizer_class, '''hf-internal-testing/tiny-random-nllb''', {})
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
											with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''):
														UpperCAmelCase__	:       List[Any]   =  self.rust_tokenizer_class.from_pretrained(A_				,				**A_)
														UpperCAmelCase__	:       str   =  self.tokenizer_class.from_pretrained(A_				,				**A_)

														UpperCAmelCase__	:       Dict   =  tempfile.mkdtemp()

														UpperCAmelCase__	:       int   =  tokenizer_r.save_pretrained(A_)
														UpperCAmelCase__	:       int   =  tokenizer_p.save_pretrained(A_)

														# Checks it save with the same files + the tokenizer.json file for the fast one
														self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files))
														UpperCAmelCase__	:       str   =  tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f)
														self.assertSequenceEqual(A_				,				A_)

														# Checks everything loads correctly in the same way
														UpperCAmelCase__	:       List[Any]   =  tokenizer_r.from_pretrained(A_)
														UpperCAmelCase__	:       Any   =  tokenizer_p.from_pretrained(A_)

														# Check special tokens are set accordingly on Rust and Python
														for key in tokenizer_pp.special_tokens_map:
																	self.assertTrue(hasattr(A_				,				A_))

														shutil.rmtree(A_)

														# Save tokenizer rust, legacy_format=True
														UpperCAmelCase__	:       Tuple   =  tempfile.mkdtemp()

														UpperCAmelCase__	:       Dict   =  tokenizer_r.save_pretrained(A_				,				legacy_format=A_)
														UpperCAmelCase__	:       List[str]   =  tokenizer_p.save_pretrained(A_)

														# Checks it save with the same files
														self.assertSequenceEqual(A_				,				A_)

														# Checks everything loads correctly in the same way
														UpperCAmelCase__	:       Optional[Any]   =  tokenizer_r.from_pretrained(A_)
														UpperCAmelCase__	:       int   =  tokenizer_p.from_pretrained(A_)

														# Check special tokens are set accordingly on Rust and Python
														for key in tokenizer_pp.special_tokens_map:
																	self.assertTrue(hasattr(A_				,				A_))

														shutil.rmtree(A_)

														# Save tokenizer rust, legacy_format=False
														UpperCAmelCase__	:       Any   =  tempfile.mkdtemp()

														UpperCAmelCase__	:       str   =  tokenizer_r.save_pretrained(A_				,				legacy_format=A_)
														UpperCAmelCase__	:       Any   =  tokenizer_p.save_pretrained(A_)

														# Checks it saved the tokenizer.json file
														self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files))

														# Checks everything loads correctly in the same way
														UpperCAmelCase__	:       Any   =  tokenizer_r.from_pretrained(A_)
														UpperCAmelCase__	:       int   =  tokenizer_p.from_pretrained(A_)

														# Check special tokens are set accordingly on Rust and Python
														for key in tokenizer_pp.special_tokens_map:
																	self.assertTrue(hasattr(A_				,				A_))

														shutil.rmtree(A_)




					@require_torch
					def 					snake_case__    (   self):




								if not self.test_seqaseq:
											return

								UpperCAmelCase__	:       List[str]   =  self.get_tokenizers()
								for tokenizer in tokenizers:
											with self.subTest(f'''{tokenizer.__class__.__name__}'''):
														# Longer text that will definitely require truncation.
														UpperCAmelCase__	:       Dict   =  [
														    ''' UN Chief Says There Is No Military Solution in Syria''',
														    ''' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for'''
														    ''' Syria is that \'there is no military solution\' to the nearly five-year conflict and more weapons'''
														    ''' will only worsen the violence and misery for millions of people.''',
														]
														UpperCAmelCase__	:       List[str]   =  [
														    '''Şeful ONU declară că nu există o soluţie militară în Siria''',
														    '''Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al'''
														    ''' Rusiei pentru Siria este că "nu există o soluţie militară" la conflictul de aproape cinci ani şi'''
														    ''' că noi arme nu vor face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.''',
														]
														try:
																	UpperCAmelCase__	:       Union[str, Any]   =  tokenizer.prepare_seqaseq_batch(
																	    src_texts=A_				,				tgt_texts=A_				,				max_length=3				,				max_target_length=10				,				return_tensors="""pt"""				,				src_lang="""eng_Latn"""				,				tgt_lang="""ron_Latn"""				,				)
														except NotImplementedError:
																	return
														self.assertEqual(batch.input_ids.shape[1]				,				3)
														self.assertEqual(batch.labels.shape[1]				,				10)
														# max_target_length will default to max_length if not specified
														UpperCAmelCase__	:       Optional[int]   =  tokenizer.prepare_seqaseq_batch(
														    A_				,				tgt_texts=A_				,				max_length=3				,				return_tensors="""pt""")
														self.assertEqual(batch.input_ids.shape[1]				,				3)
														self.assertEqual(batch.labels.shape[1]				,				3)

														UpperCAmelCase__	:       Any   =  tokenizer.prepare_seqaseq_batch(
														    src_texts=A_				,				max_length=3				,				max_target_length=10				,				return_tensors="""pt""")
														self.assertEqual(batch_encoder_only.input_ids.shape[1]				,				3)
														self.assertEqual(batch_encoder_only.attention_mask.shape[1]				,				3)
														self.assertNotIn("""decoder_input_ids"""				,				A_)




					@unittest.skip("""Unfortunately way too slow to build a BPE with SentencePiece.""")
					def 					snake_case__    (   self):
								pass




					def 					snake_case__    (   self):




								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
											with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''):
														UpperCAmelCase__	:       Optional[int]   =  [AddedToken("""<special>"""				,				lstrip=A_)]

														UpperCAmelCase__	:       Union[str, Any]   =  self.rust_tokenizer_class.from_pretrained(
														    A_				,				additional_special_tokens=A_				,				**A_)
														UpperCAmelCase__	:       str   =  tokenizer_r.encode("""Hey this is a <special> token""")

														UpperCAmelCase__	:       List[Any]   =  tokenizer_r.encode("""<special>"""				,				add_special_tokens=A_)[0]

														self.assertTrue(special_token_id in r_output)

														if self.test_slow_tokenizer:
																	UpperCAmelCase__	:       Optional[Any]   =  self.rust_tokenizer_class.from_pretrained(
																	    A_				,				additional_special_tokens=A_				,				**A_				,				)
																	UpperCAmelCase__	:       List[str]   =  self.tokenizer_class.from_pretrained(
																	    A_				,				additional_special_tokens=A_				,				**A_)

																	UpperCAmelCase__	:       Any   =  tokenizer_p.encode("""Hey this is a <special> token""")

																	UpperCAmelCase__	:       Optional[Any]   =  tokenizer_cr.encode("""Hey this is a <special> token""")

																	self.assertEqual(A_				,				A_)
																	self.assertEqual(A_				,				A_)
																	self.assertTrue(special_token_id in p_output)
																	self.assertTrue(special_token_id in cr_output)


@require_torch
@require_sentencepiece
@require_tokenizers
class 		_snake_case       (  unittest.TestCase						):
					lowerCAmelCase   :Optional[int]				=       '''facebook/nllb-200-distilled-600M'''
					lowerCAmelCase   :List[str]				=       [
					    ''' UN Chief Says There Is No Military Solution in Syria''',
					    ''' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for Syria is that "there is no military solution" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.''',
					]
					lowerCAmelCase   :List[str]				=       [
					    '''Şeful ONU declară că nu există o soluţie militară în Siria''',
					    '''Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei'''
					    ''' pentru Siria este că "nu există o soluţie militară" la conflictul de aproape cinci ani şi că noi arme nu vor'''
					    ''' face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.''',
					]
					lowerCAmelCase   :Dict				=       [
					    256_047,
					    16_297,
					    134_408,
					    8_165,
					    248_066,
					    14_734,
					    950,
					    1_135,
					    105_721,
					    3_573,
					    83,
					    27_352,
					    108,
					    49_486,
					    2,
					]




					@classmethod
					def 					snake_case__    (   cls):
								UpperCAmelCase__	:       NllbTokenizer   =  NllbTokenizer.from_pretrained(
								    cls.checkpoint_name				,				src_lang="""eng_Latn"""				,				tgt_lang="""ron_Latn""")
								UpperCAmelCase__	:       List[str]   =  1
								return cls




					def 					snake_case__    (   self):
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ace_Arab"""]				,				25_6001)
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ace_Latn"""]				,				25_6002)
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""fra_Latn"""]				,				25_6057)




					def 					snake_case__    (   self):
								UpperCAmelCase__	:       Tuple   =  self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
								self.assertListEqual(self.expected_src_tokens				,				A_)




					def 					snake_case__    (   self):
								self.assertIn(A_				,				self.tokenizer.all_special_ids)
								# fmt: off
								UpperCAmelCase__	:       Tuple   =  [RO_CODE, 4254, 9_8068, 11_2923, 3_9072, 3909, 713, 10_2767, 26, 1_7314, 3_5642, 1_4683, 3_3118, 2022, 6_6987, 2, 25_6047]
								# fmt: on

								UpperCAmelCase__	:       Optional[Any]   =  self.tokenizer.decode(A_				,				skip_special_tokens=A_)
								UpperCAmelCase__	:       Tuple   =  self.tokenizer.decode(generated_ids[1:]				,				skip_special_tokens=A_)
								self.assertEqual(A_				,				A_)
								self.assertNotIn(self.tokenizer.eos_token				,				A_)




					def 					snake_case__    (   self):
								UpperCAmelCase__	:       Optional[Any]   =  ['''this is gunna be a long sentence ''' * 20]
								assert isinstance(src_text[0]				,				A_)
								UpperCAmelCase__	:       List[str]   =  10
								UpperCAmelCase__	:       int   =  self.tokenizer(A_				,				max_length=A_				,				truncation=A_).input_ids[0]
								self.assertEqual(ids[-1]				,				2)
								self.assertEqual(ids[0]				,				A_)
								self.assertEqual(len(A_)				,				A_)




					def 					snake_case__    (   self):
								self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""])				,				[25_6203, 3])




					def 					snake_case__    (   self):
								UpperCAmelCase__	:       Tuple   =  tempfile.mkdtemp()
								UpperCAmelCase__	:       int   =  self.tokenizer.fairseq_tokens_to_ids
								self.tokenizer.save_pretrained(A_)
								UpperCAmelCase__	:       List[Any]   =  NllbTokenizer.from_pretrained(A_)
								self.assertDictEqual(new_tok.fairseq_tokens_to_ids				,				A_)




					@require_torch
					def 					snake_case__    (   self):
								UpperCAmelCase__	:       Union[str, Any]   =  self.tokenizer(
								    self.src_text				,				text_target=self.tgt_text				,				padding=A_				,				truncation=A_				,				max_length=len(self.expected_src_tokens)				,				return_tensors="""pt"""				,				)
								UpperCAmelCase__	:       str   =  shift_tokens_right(
								    batch["""labels"""]				,				self.tokenizer.pad_token_id				,				self.tokenizer.lang_code_to_id["""ron_Latn"""])

								self.assertIsInstance(A_				,				A_)

								self.assertEqual((2, 15)				,				batch.input_ids.shape)
								self.assertEqual((2, 15)				,				batch.attention_mask.shape)
								UpperCAmelCase__	:       str   =  batch.input_ids.tolist()[0]
								self.assertListEqual(self.expected_src_tokens				,				A_)
								self.assertEqual(A_				,				batch.decoder_input_ids[0, 0])  # EOS
								# Test that special tokens are reset
								self.assertEqual(self.tokenizer.prefix_tokens				,				[EN_CODE])
								self.assertEqual(self.tokenizer.suffix_tokens				,				[self.tokenizer.eos_token_id])




					def 					snake_case__    (   self):
								UpperCAmelCase__	:       Optional[int]   =  self.tokenizer(self.src_text				,				padding=A_				,				truncation=A_				,				max_length=3				,				return_tensors="""pt""")
								UpperCAmelCase__	:       str   =  self.tokenizer(
								    text_target=self.tgt_text				,				padding=A_				,				truncation=A_				,				max_length=10				,				return_tensors="""pt""")
								UpperCAmelCase__	:       Optional[int]   =  targets['''input_ids''']
								UpperCAmelCase__	:       Optional[Any]   =  shift_tokens_right(
								    A_				,				self.tokenizer.pad_token_id				,				decoder_start_token_id=self.tokenizer.lang_code_to_id[self.tokenizer.tgt_lang]				,				)

								self.assertEqual(batch.input_ids.shape[1]				,				3)
								self.assertEqual(batch.decoder_input_ids.shape[1]				,				10)




					@require_torch
					def 					snake_case__    (   self):
								UpperCAmelCase__	:       str   =  self.tokenizer._build_translation_inputs(
								    """A test"""				,				return_tensors="""pt"""				,				src_lang="""eng_Latn"""				,				tgt_lang="""fra_Latn""")

								self.assertEqual(
								    nested_simplify(A_)				,				{
								        # A, test, EOS, en_XX
								        """input_ids""": [[25_6047, 70, 7356, 2]],
								        """attention_mask""": [[1, 1, 1, 1]],
								        # ar_AR
								        """forced_bos_token_id""": 25_6057,
								    }				,				)




					@require_torch
					def 					snake_case__    (   self):
								UpperCAmelCase__	:       Dict   =  True
								UpperCAmelCase__	:       Tuple   =  self.tokenizer(
								    """UN Chief says there is no military solution in Syria"""				,				src_lang="""eng_Latn"""				,				tgt_lang="""fra_Latn""")
								self.assertEqual(
								    inputs.input_ids				,				[1_6297, 13_4408, 2_5653, 6370, 248, 254, 10_3929, 9_4995, 108, 4_9486, 2, 25_6047])

								UpperCAmelCase__	:       Dict   =  False
								UpperCAmelCase__	:       int   =  self.tokenizer(
								    """UN Chief says there is no military solution in Syria"""				,				src_lang="""eng_Latn"""				,				tgt_lang="""fra_Latn""")
								self.assertEqual(
								    inputs.input_ids				,				[25_6047, 1_6297, 13_4408, 2_5653, 6370, 248, 254, 10_3929, 9_4995, 108, 4_9486, 2])

"""simple docstring"""




def 			_lowerCAmelCase		(		_UpperCamelCase    ):






  """simple docstring"""



  stooge(_UpperCamelCase			,					0			,					len(_UpperCamelCase    ) - 1    )
  return arr




def 			_lowerCAmelCase		(		_UpperCamelCase			,					_UpperCamelCase			,					_UpperCamelCase    ):






  """simple docstring"""



  if i >= h:
    return

  # If first element is smaller than the last then swap them
  if arr[i] > arr[h]:
    _lowercase			,					_lowercase:      Optional[Any]   			=  arr[h], arr[i]

  # If there are more than 2 elements in the array
  if h - i + 1 > 2:
    _lowercase:      Tuple   			=  (int)((h - i + 1) / 3    )

    # Recursively sort first 2/3 elements
    stooge(_UpperCamelCase			,					_UpperCamelCase			,					(h - t)    )

    # Recursively sort last 2/3 elements
    stooge(_UpperCamelCase			,					i + t			,					(_UpperCamelCase)    )

    # Recursively sort first 2/3 elements
    stooge(_UpperCamelCase			,					_UpperCamelCase			,					(h - t)    )


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